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1.
Semi-supervised discriminative classification with application to tumorous tissues segmentation of MR brain images 总被引:1,自引:1,他引:0
Yangqiu Song Changshui Zhang Jianguo Lee Fei Wang Shiming Xiang Dan Zhang 《Pattern Analysis & Applications》2009,12(2):99-115
Due to the large data size of 3D MR brain images and the blurry boundary of the pathological tissues, tumor segmentation work
is difficult. This paper introduces a discriminative classification algorithm for semi-automated segmentation of brain tumorous
tissues. The classifier uses interactive hints to obtain models to classify normal and tumor tissues. A non-parametric Bayesian
Gaussian random field in the semi-supervised mode is implemented. Our approach uses both labeled data and a subset of unlabeled
data sampling from 2D/3D images for training the model. Fast algorithm is also developed. Experiments show that our approach
produces satisfactory segmentation results comparing to the manually labeled results by experts.
Yangqiu Song received his B.S. degree from Department of Automation, Tsinghua University, China, in 2003. He is currently a Ph.D. candidate in Department of Automation, Tsinghua University. His research interests focus on machine learning and its applications. Changshui Zhang received his B.S. degree in Mathematics from Peking University, China, in 1986, and Ph.D. degree from Department of Automation, Tsinghua University in 1992. He is currently a professor of Department of Automation, Tsinghua University. He is an Associate Editor of the journal Pattern Recognition. His interests include artificial intelligence, image processing, pattern recognition, machine learning, evolutionary computation and complex system analysis, etc. Jianguo Lee received his B.S. degree from Department of Automatic Control, Huazhong University of Science and Technology (HUST), China, in 2001 and Ph.D. degree in Department of Automation, Tsinghua University in 2006. He is currently a researcher in Intel China Reasearch Center. His research interests focus on machine learning and its applications. Fei Wang is a Ph.D. candidate from Department of Automation, Tsinghua University, Beijing, China. His main research interests include machine learning, data mining, and pattern recognition. Shiming Xiang received his B.S. degree from Department of Mathematics of Chongqing Normal University, China, in 1993 and M.S. degree from Department of Mechanics and Mathematics of Chongqing University, China, in 1996 and Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences, China, in 2004. He is currently a postdoctoral scholar in Department of Automation, Tsinghua University. His interests include computer vision, pattern recognition, machine learning, etc. Dan Zhang received his B.S. degree in Electronic and Information Engineering from Nanjing University of Posts and Telecommunications in 2005. He is now a Master candidate from Department of Automation, Tsinghua University, Beijing, China. His research interests include pattern recognition, machine learning, and blind signal separation. 相似文献
Changshui ZhangEmail: |
Yangqiu Song received his B.S. degree from Department of Automation, Tsinghua University, China, in 2003. He is currently a Ph.D. candidate in Department of Automation, Tsinghua University. His research interests focus on machine learning and its applications. Changshui Zhang received his B.S. degree in Mathematics from Peking University, China, in 1986, and Ph.D. degree from Department of Automation, Tsinghua University in 1992. He is currently a professor of Department of Automation, Tsinghua University. He is an Associate Editor of the journal Pattern Recognition. His interests include artificial intelligence, image processing, pattern recognition, machine learning, evolutionary computation and complex system analysis, etc. Jianguo Lee received his B.S. degree from Department of Automatic Control, Huazhong University of Science and Technology (HUST), China, in 2001 and Ph.D. degree in Department of Automation, Tsinghua University in 2006. He is currently a researcher in Intel China Reasearch Center. His research interests focus on machine learning and its applications. Fei Wang is a Ph.D. candidate from Department of Automation, Tsinghua University, Beijing, China. His main research interests include machine learning, data mining, and pattern recognition. Shiming Xiang received his B.S. degree from Department of Mathematics of Chongqing Normal University, China, in 1993 and M.S. degree from Department of Mechanics and Mathematics of Chongqing University, China, in 1996 and Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences, China, in 2004. He is currently a postdoctoral scholar in Department of Automation, Tsinghua University. His interests include computer vision, pattern recognition, machine learning, etc. Dan Zhang received his B.S. degree in Electronic and Information Engineering from Nanjing University of Posts and Telecommunications in 2005. He is now a Master candidate from Department of Automation, Tsinghua University, Beijing, China. His research interests include pattern recognition, machine learning, and blind signal separation. 相似文献
2.
NNSRM is an implementation of the structural risk minimization (SRM) principle using the nearest neighbor (NN) rule, and linear
discriminant analysis (LDA) is a dimension-reducing method, which is usually used in classifications. This paper combines
the two methods for face recognition. We first project the face images into a PCA subspace, then project the results into
a much lower-dimensional LDA subspace, and then use an NNSRM classifier to recognize them in the LDA subspace. Experimental
results demonstrate that the combined method can achieve a better performance than NN by selecting different distances and
a comparable performance with SVM but costing less computational time.
Danian Zheng received his Bachelor degree in Computer Science and Technology in 2002 from Tsinghua University, Beijing, China. He received his Master degree and Doctoral degree in Computer Science and Technology in 2006 from Tsinghua University. He is currently a researcher in Fujitsu R&D Center Co. Ltd, Beijing, China. His research interests are mainly in the areas of support vector machines, kernel methods and their applications. Meng Na received her Bachelor degree in Computer Science and Technology in 2003 from Northeastern, China. Since 2003 she has been pursuing the Master degree and the Doctoral degree at the Department of Computer Science and Technology at Tsinghua University. Her research interests are in the area of image processing, pattern recognition, and virtual human. Jiaxin Wang received his Bachelor degree in Automatic Control in 1965 from Beijing University of Aeronautics and Astronautics, his Master degree in Computer Science and Technology in 1981 from Tsinghua University, Beijing, China, and his Doctoral degree in 1996 from Engineering Faculty of Vrije Universiteit Brussel, Belgium. He is currently a professor of Department of Computer Science and Technology, Tsinghua University. His research interests are in the areas of artificial intelligence, intelligent control and robotics, machine learning, pattern recognition, image processing and virtual reality. 相似文献
Jiaxin Wang (Corresponding author)Email: |
Danian Zheng received his Bachelor degree in Computer Science and Technology in 2002 from Tsinghua University, Beijing, China. He received his Master degree and Doctoral degree in Computer Science and Technology in 2006 from Tsinghua University. He is currently a researcher in Fujitsu R&D Center Co. Ltd, Beijing, China. His research interests are mainly in the areas of support vector machines, kernel methods and their applications. Meng Na received her Bachelor degree in Computer Science and Technology in 2003 from Northeastern, China. Since 2003 she has been pursuing the Master degree and the Doctoral degree at the Department of Computer Science and Technology at Tsinghua University. Her research interests are in the area of image processing, pattern recognition, and virtual human. Jiaxin Wang received his Bachelor degree in Automatic Control in 1965 from Beijing University of Aeronautics and Astronautics, his Master degree in Computer Science and Technology in 1981 from Tsinghua University, Beijing, China, and his Doctoral degree in 1996 from Engineering Faculty of Vrije Universiteit Brussel, Belgium. He is currently a professor of Department of Computer Science and Technology, Tsinghua University. His research interests are in the areas of artificial intelligence, intelligent control and robotics, machine learning, pattern recognition, image processing and virtual reality. 相似文献
3.
Antonio Ciampi Yves Lechevallier Manuel Castejón Limas Ana González Marcos 《Pattern Analysis & Applications》2008,11(2):199-220
The problem of clustering subpopulations on the basis of samples is considered within a statistical framework: a distribution
for the variables is assumed for each subpopulation and the dissimilarity between any two populations is defined as the likelihood
ratio statistic which compares the hypothesis that the two subpopulations differ in the parameter of their distributions to
the hypothesis that they do not. A general algorithm for the construction of a hierarchical classification is described which
has the important property of not having inversions in the dendrogram. The essential elements of the algorithm are specified
for the case of well-known distributions (normal, multinomial and Poisson) and an outline of the general parametric case is
also discussed. Several applications are discussed, the main one being a novel approach to dealing with massive data in the
context of a two-step approach. After clustering the data in a reasonable number of ‘bins’ by a fast algorithm such as k-Means, we apply a version of our algorithm to the resulting bins. Multivariate normality for the means calculated on each
bin is assumed: this is justified by the central limit theorem and the assumption that each bin contains a large number of
units, an assumption generally justified when dealing with truly massive data such as currently found in modern data analysis.
However, no assumption is made about the data generating distribution.
Antonio Ciampi received his M.Sc. and Ph.D. degrees from Queen's University, Kingston, Ontario, Canada in 1973. He taught at the University of Zambia from 1973 to 1977. Returning to Canada he worked as statitician in the Treasury of the Ontario Government. From 1978 to 1985, he was Senior Scientist in the Ontario Cancer Institute, Toronto, and taught at the University of Toronto. In 1985 he moved to Montreal where he is Associate Professor in the Department of Epidemiology, Biostatistics and Occupational Health, McGill University. He has also been Senior Scientist of the Montreal Children's Hospital Research Instititue, in the Montreal Heart Institute and in the St. Mary's Hospital Community Health Research Unit. His research interest include Statistical Learning, Data Mining and Statistical Modeling. Yves Lechevallier In 1976 he joined the INRIA where he was engaged in the project of Clustering and Pattern Recognition. Since 1988 he has been teaching Clustering, Neural Network and Data Mining at the University of PARIS-IX, CNAM and ENSAE. He specializes in Mathematical Statistics, Applied Statistics, Data Analysis and Classification. Current Research Interests: (1) Clustering algorithm (Dynamic Clustering Method, Kohonen Maps, Divisive Clustering Method); (2) Discrimination Problems and Decision Tree Methods; Build an efficient Neural Network by Classification Tree. Manuel Castejón Limas received his engineering degree from the Universidad de Oviedo in 1999 and his Ph.D. degree from the Universidad de La Rioja in 2004. From 2002 he teaches project management at the Universidad de Leon. His research is oriented towards the development of data analysis procedures that may aid project managers on their decision making processes. Ana González Marcos received her M.Sc. and Ph.D. degrees from the University of La Rioja, Spain. In 2003, she joined the University of León, Spain, where she works as a Lecturer in the Department of Mechanical, Informatic and Aerospace Engineering. Her research interests include the application of multivariate analysis and artificial intelligence techniques in order to improve the quality of industrial processes. 相似文献
Antonio CiampiEmail: |
Antonio Ciampi received his M.Sc. and Ph.D. degrees from Queen's University, Kingston, Ontario, Canada in 1973. He taught at the University of Zambia from 1973 to 1977. Returning to Canada he worked as statitician in the Treasury of the Ontario Government. From 1978 to 1985, he was Senior Scientist in the Ontario Cancer Institute, Toronto, and taught at the University of Toronto. In 1985 he moved to Montreal where he is Associate Professor in the Department of Epidemiology, Biostatistics and Occupational Health, McGill University. He has also been Senior Scientist of the Montreal Children's Hospital Research Instititue, in the Montreal Heart Institute and in the St. Mary's Hospital Community Health Research Unit. His research interest include Statistical Learning, Data Mining and Statistical Modeling. Yves Lechevallier In 1976 he joined the INRIA where he was engaged in the project of Clustering and Pattern Recognition. Since 1988 he has been teaching Clustering, Neural Network and Data Mining at the University of PARIS-IX, CNAM and ENSAE. He specializes in Mathematical Statistics, Applied Statistics, Data Analysis and Classification. Current Research Interests: (1) Clustering algorithm (Dynamic Clustering Method, Kohonen Maps, Divisive Clustering Method); (2) Discrimination Problems and Decision Tree Methods; Build an efficient Neural Network by Classification Tree. Manuel Castejón Limas received his engineering degree from the Universidad de Oviedo in 1999 and his Ph.D. degree from the Universidad de La Rioja in 2004. From 2002 he teaches project management at the Universidad de Leon. His research is oriented towards the development of data analysis procedures that may aid project managers on their decision making processes. Ana González Marcos received her M.Sc. and Ph.D. degrees from the University of La Rioja, Spain. In 2003, she joined the University of León, Spain, where she works as a Lecturer in the Department of Mechanical, Informatic and Aerospace Engineering. Her research interests include the application of multivariate analysis and artificial intelligence techniques in order to improve the quality of industrial processes. 相似文献
4.
Chu-Yin Chang Anthony A. Maciejewski Venkataramanan Balakrishnan Rodney G. Roberts Kishor Saitwal 《Pattern Analysis & Applications》2007,10(1):15-31
Eigendecomposition-based techniques are popular for a number of computer vision problems, e.g., object and pose estimation,
because they are purely appearance based and they require few on-line computations. Unfortunately, they also typically require
an unobstructed view of the object whose pose is being detected. The presence of occlusion and background clutter precludes
the use of the normalizations that are typically applied and significantly alters the appearance of the object under detection.
This work presents an algorithm that is based on applying eigendecomposition to a quadtree representation of the image dataset
used to describe the appearance of an object. This allows decisions concerning the pose of an object to be based on only those
portions of the image in which the algorithm has determined that the object is not occluded. The accuracy and computational
efficiency of the proposed approach is evaluated on 16 different objects with up to 50% of the object being occluded and on
images of ships in a dockyard.
Chu-Yin Chang received the B.S. degree in mechanical engineering from National Central University, Chung-Li, Taiwan, ROC, in 1988, the M.S. degree in electrical engineering from the University of California, Davis, in 1993, and the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, in 1999. From 1999--2002, he was a Machine Vision Systems Engineer with Semiconductor Technologies and Instruments, Inc., Plano, TX. He is currently the Vice President of Energid Technologies, Cambridge, MA, USA. His research interests include computer vision, computer graphics, and robotics. Anthony A. Maciejewski received the BSEE, M.S., and Ph.D. degrees from Ohio State University in 1982, 1984, and 1987. From 1988 to 2001, he was a professor of Electrical and Computer Engineering at Purdue University, West Lafayette. He is currently the Department Head of Electrical and Computer Engineering at Colorado State University. He is a Fellow of the IEEE. A complete vita is available at: Venkataramanan Balakrishnan is Professor and Associate Head of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana. He received the B.Tech degree in electronics and communication and the President of India Gold Medal from the Indian Institute of Technology, Madras, in 1985. He then attended Stanford University, where he received the M.S. degree in statistics and the Ph.D. degree in electrical engineering in 1992. He joined Purdue University in 1994 after post-doctoral research at Stanford, CalTech and the University of Maryland. His primary research interests are in convex optimization and large-scale numerical algebra, applied to engineering problems. Rodney G. Roberts received B.S. degrees in Electrical Engineering and Mathematics from Rose-Hulman Institute of Technology in 1987 and an MSEE and Ph.D. in Electrical Engineering from Purdue University in 1988 and 1992, respectively. From 1992 until 1994, he was a National Research Council Fellow at Wright Patterson Air Force Base in Dayton, Ohio. Since 1994 he has been at the Florida A&M University---Florida State University College of Engineering where he is currently a Professor of Electrical and Computer Engineering. His research interests are in the areas of robotics and image processing. Kishor Saitwal received the Bachelor of Engineering (B.E.) degree in Instrumentation and Controls from Vishwakarma Institute of Technology, Pune, India, in 1998. He was ranked Third in the Pune University and was recipient of National Talent Search scholarship. He received the M.S. and Ph.D. degrees from the Electrical and Computer Engineering department, Colorado State University, Fort Collins, in 2001 and 2006, respectively. He is currently with Behavioral Recognition Systems, Inc. performing research in computer aided video surveillance systems. His research interests include image/video processing, computer vision, and robotics. 相似文献
Anthony A. MaciejewskiEmail: |
Chu-Yin Chang received the B.S. degree in mechanical engineering from National Central University, Chung-Li, Taiwan, ROC, in 1988, the M.S. degree in electrical engineering from the University of California, Davis, in 1993, and the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, in 1999. From 1999--2002, he was a Machine Vision Systems Engineer with Semiconductor Technologies and Instruments, Inc., Plano, TX. He is currently the Vice President of Energid Technologies, Cambridge, MA, USA. His research interests include computer vision, computer graphics, and robotics. Anthony A. Maciejewski received the BSEE, M.S., and Ph.D. degrees from Ohio State University in 1982, 1984, and 1987. From 1988 to 2001, he was a professor of Electrical and Computer Engineering at Purdue University, West Lafayette. He is currently the Department Head of Electrical and Computer Engineering at Colorado State University. He is a Fellow of the IEEE. A complete vita is available at: Venkataramanan Balakrishnan is Professor and Associate Head of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana. He received the B.Tech degree in electronics and communication and the President of India Gold Medal from the Indian Institute of Technology, Madras, in 1985. He then attended Stanford University, where he received the M.S. degree in statistics and the Ph.D. degree in electrical engineering in 1992. He joined Purdue University in 1994 after post-doctoral research at Stanford, CalTech and the University of Maryland. His primary research interests are in convex optimization and large-scale numerical algebra, applied to engineering problems. Rodney G. Roberts received B.S. degrees in Electrical Engineering and Mathematics from Rose-Hulman Institute of Technology in 1987 and an MSEE and Ph.D. in Electrical Engineering from Purdue University in 1988 and 1992, respectively. From 1992 until 1994, he was a National Research Council Fellow at Wright Patterson Air Force Base in Dayton, Ohio. Since 1994 he has been at the Florida A&M University---Florida State University College of Engineering where he is currently a Professor of Electrical and Computer Engineering. His research interests are in the areas of robotics and image processing. Kishor Saitwal received the Bachelor of Engineering (B.E.) degree in Instrumentation and Controls from Vishwakarma Institute of Technology, Pune, India, in 1998. He was ranked Third in the Pune University and was recipient of National Talent Search scholarship. He received the M.S. and Ph.D. degrees from the Electrical and Computer Engineering department, Colorado State University, Fort Collins, in 2001 and 2006, respectively. He is currently with Behavioral Recognition Systems, Inc. performing research in computer aided video surveillance systems. His research interests include image/video processing, computer vision, and robotics. 相似文献
5.
This paper
focuses on human behavior recognition where the main problem is to bridge the
semantic gap between the analogue observations of the real world and the
symbolic world of human interpretation. For that, a fusion architecture based
on the Transferable Belief Model framework is proposed and applied to action
recognition of an athlete in video sequences of athletics meeting with moving
camera. Relevant features are extracted from videos, based on both the camera
motion analysis and the tracking of particular points on the athlete’s
silhouette. Some models of interpretation are used to link the numerical
features to the symbols to be recognized, which are running, jumping and
falling actions. A Temporal Belief Filter is then used to improve the
robustness of action recognition. The proposed approach demonstrates good
performance when tested on real videos of athletics sports videos (high jumps,
pole vaults, triple jumps and long jumps) acquired by a moving camera and
different view angles. The proposed system is also compared to Bayesian
Networks.
Emmanuel Ramasso is currently pursuing a PhD at GIPSA-lab, Department of Images and Signal located in Grenoble, France. He received both his BS degree in Electrical Engineering and Control Theory and his MS degree in Computer Science in 2004 from Ecole Polytechnique de Savoie (Annecy, France). His research interests include Sequential Data Analysis, Transferable Belief Model, Fusion, Image and Videos Analysis and Human Motion Analysis. Costas Panagiotakis was born in Heraklion, Crete, Greece in 1979. He received the BS and the MS degrees in Computer Science from University of Crete in 2001 and 2003, respectively. Currently, he is a PhD candidate in Computer Science at University of Crete. His research interests include computer vision, image and video analysis, motion analysis and synthesis, computer graphics, computational geometry and signal processing. Denis Pellerin received the Engineering degree in Electrical Engineering in 1984 and the PhD degree in 1988 from the Institut National des Sciences Appliquées, Lyon, France. He is currently a full Professor at the Université Joseph Fourier, Grenoble, France. His research interests include visual perception, motion analysis in image sequences, video analysis, and indexing. Michèle Rombaut is currently a full Professor at the Université Joseph Fourier, Grenoble, France. Her research interests include Data Fusion, Sequential Data Analysis, High Level Interpretation, Image and Video Analysis. 相似文献
M. RombautEmail: |
Emmanuel Ramasso is currently pursuing a PhD at GIPSA-lab, Department of Images and Signal located in Grenoble, France. He received both his BS degree in Electrical Engineering and Control Theory and his MS degree in Computer Science in 2004 from Ecole Polytechnique de Savoie (Annecy, France). His research interests include Sequential Data Analysis, Transferable Belief Model, Fusion, Image and Videos Analysis and Human Motion Analysis. Costas Panagiotakis was born in Heraklion, Crete, Greece in 1979. He received the BS and the MS degrees in Computer Science from University of Crete in 2001 and 2003, respectively. Currently, he is a PhD candidate in Computer Science at University of Crete. His research interests include computer vision, image and video analysis, motion analysis and synthesis, computer graphics, computational geometry and signal processing. Denis Pellerin received the Engineering degree in Electrical Engineering in 1984 and the PhD degree in 1988 from the Institut National des Sciences Appliquées, Lyon, France. He is currently a full Professor at the Université Joseph Fourier, Grenoble, France. His research interests include visual perception, motion analysis in image sequences, video analysis, and indexing. Michèle Rombaut is currently a full Professor at the Université Joseph Fourier, Grenoble, France. Her research interests include Data Fusion, Sequential Data Analysis, High Level Interpretation, Image and Video Analysis. 相似文献
6.
In this paper we present a novel methodology based on non-parametric deformable prototype templates for reconstructing the
outline of a shape from a degraded image. Our method is versatile and fast and has the potential to provide an automatic procedure
for classifying pathologies. We test our approach on synthetic and real data from a variety of medical and biological applications.
In these studies it is important to reconstruct accurately the shape of the object under investigation from very noisy data.
Here we assume that we have some prior knowledge about the object outline represented by a prototype shape. Our procedure
deforms this shape by means of non-affine transformations and the contour is reconstructed by minimizing a newly developed
objective function that depends on the transformation parameters. We introduce an iterative template deformation procedure
in which the scale of the deformation decreases as the algorithm proceeds. We compare our results with those from a Gaussian
Mixture Model segmentation and two state-of-the-art Level Set methods. This comparison shows that the proposed procedure performs
consistently well on both real and simulated data. As a by-product we develop a new filter that recovers the connectivity
of a shape.
Francesco de Pasquale received his Ph.D. in Applied Statistics from the University of Plymouth, United Kingdom in 2004 discussing a thesis on Bayesian and Template based methods for image analysis. Since his degree in Physics obtained at the University of Rome ‘La Sapienza’in 1999 his work has been focused on developing models and methods for Magnetic Resonance Imaging, in particular image registration, classification and segmentation in a Bayesian framework. After being appointed a 2-year contract as a Lecturer at the University of Plymouth from 2003 to 2004 he is now a post-Doc researcher at the ITAB, Institute for Advanced Biomedical Technologies, University of Chieti, Italy and he works on the analysis of fMRI and MEG data. Julian Stander was born in Plymouth, UK in 1964. He received a BA in Mathematics with first class honours from University of Oxford in 1987, a Diploma in Mathematical Statistics with distinction from University of Cambridge in 1988, and a PhD from University of Bath in 1992. He has been a lecturer at the School of Mathematics and Statistics, University of Plymouth, since 1993, and was promoted to Reader in 2006. His fields of interest are: applications of statistics including image analysis, spatial modelling and disclosure limitation. He has published over 20 refereed journal articles. 相似文献
Francesco de PasqualeEmail: |
Francesco de Pasquale received his Ph.D. in Applied Statistics from the University of Plymouth, United Kingdom in 2004 discussing a thesis on Bayesian and Template based methods for image analysis. Since his degree in Physics obtained at the University of Rome ‘La Sapienza’in 1999 his work has been focused on developing models and methods for Magnetic Resonance Imaging, in particular image registration, classification and segmentation in a Bayesian framework. After being appointed a 2-year contract as a Lecturer at the University of Plymouth from 2003 to 2004 he is now a post-Doc researcher at the ITAB, Institute for Advanced Biomedical Technologies, University of Chieti, Italy and he works on the analysis of fMRI and MEG data. Julian Stander was born in Plymouth, UK in 1964. He received a BA in Mathematics with first class honours from University of Oxford in 1987, a Diploma in Mathematical Statistics with distinction from University of Cambridge in 1988, and a PhD from University of Bath in 1992. He has been a lecturer at the School of Mathematics and Statistics, University of Plymouth, since 1993, and was promoted to Reader in 2006. His fields of interest are: applications of statistics including image analysis, spatial modelling and disclosure limitation. He has published over 20 refereed journal articles. 相似文献
7.
Maria Petrou Alireza Talebpour Alexander Kadyrov 《Pattern Analysis & Applications》2007,10(2):101-114
We argue that in order to understand which features are used by humans to group textures, one must start by computing thousands
of features of diverse nature, and select from those features those that allow the reproduction of perceptual groups or perceptual
ranking created by humans. We use the Trace transform to produce such features here. We compare these features with those
produced from the co-occurrence matrix and its variations. We show that when one is not interested in reproducing human behaviour,
the elements of the co-occurrence matrix used as features perform best in terms of texture classification accuracy. However,
these features cannot be “trained” or “selected” to imitate human ranking, while the features produced from the Trace transform
can. We attribute this to the diverse nature of the features computed from the Trace transform.
Maria Petrou studied Physics at the Aristotle University of Thessaloniki, Greece, Applied Mathematics in Cambridge and she did her Ph.D. in the Institute of Astronomy in Cambridge, UK. She is currently the Professor of Signal Processing and the Head of the Communications and Signal Processing Group at Imperial College. She has published more than 300 scientific papers, on Astronomy, Remote Sensing, Computer Vision, Machine Learning, Colour analysis, Industrial Inspection, and Medical Signal and Image Processing. She has co-authored two books “Image Processing: the fundamentals” and “Image Processing: Dealing with texture” both published by John Wiley in 1999 and 2006, respectively. She is a Fellow of the Royal Academy of Engineering, Fellow of IEE, Fellow of IAPR, Senior member of IEEE and a Distinguished Fellow of the British Machine Vision Association. Alireza Talebpour worked for several years in the private sector after his first degree in Electrical Engineering in Iran. He obtained his Ph.D. in image processing from Surrey University in 2004, and since then he has been a lecturer at Shahid Beheshti University in Iran. His research interests are in multimedia and signal and image processing. Alexander Kadyrov obtained his Ph.D. in Mathematics, in 1983 from St Petersburg University. From 1979 to 1997 he held various research and teaching positions at Penza State University, Russia. He started working on computer vision in 1998. He has authored or co-authored about 60 papers, textbooks and inventions. 相似文献
Maria PetrouEmail: |
Maria Petrou studied Physics at the Aristotle University of Thessaloniki, Greece, Applied Mathematics in Cambridge and she did her Ph.D. in the Institute of Astronomy in Cambridge, UK. She is currently the Professor of Signal Processing and the Head of the Communications and Signal Processing Group at Imperial College. She has published more than 300 scientific papers, on Astronomy, Remote Sensing, Computer Vision, Machine Learning, Colour analysis, Industrial Inspection, and Medical Signal and Image Processing. She has co-authored two books “Image Processing: the fundamentals” and “Image Processing: Dealing with texture” both published by John Wiley in 1999 and 2006, respectively. She is a Fellow of the Royal Academy of Engineering, Fellow of IEE, Fellow of IAPR, Senior member of IEEE and a Distinguished Fellow of the British Machine Vision Association. Alireza Talebpour worked for several years in the private sector after his first degree in Electrical Engineering in Iran. He obtained his Ph.D. in image processing from Surrey University in 2004, and since then he has been a lecturer at Shahid Beheshti University in Iran. His research interests are in multimedia and signal and image processing. Alexander Kadyrov obtained his Ph.D. in Mathematics, in 1983 from St Petersburg University. From 1979 to 1997 he held various research and teaching positions at Penza State University, Russia. He started working on computer vision in 1998. He has authored or co-authored about 60 papers, textbooks and inventions. 相似文献
8.
Vasileios K. Pothos Christos Theoharatos Evangelos Zygouris George Economou 《Pattern Analysis & Applications》2008,11(2):117-129
Texture classification is an important problem in image analysis. In the present study, an efficient strategy for classifying
texture images is introduced and examined within a distributional-statistical framework. Our approach incorporates the multivariate
Wald–Wolfowitz test (WW-test), a non-parametric statistical test that measures the similarity between two different sets of
multivariate data, which is utilized here for comparing texture distributions. By summarizing the texture information using
standard feature extraction methodologies, the similarity measure provides a comprehensive estimate of the match between different
images based on graph theory. The proposed “distributional metric” is shown to handle efficiently the texture-space dimensionality
and the limited sample size drawn from a given image. The experimental results, from the application on a typical texture
database, clearly demonstrate the effectiveness of our approach and its superiority over other well-established texture distribution
(dis)similarity metrics. In addition, its performance is used to evaluate several approaches for texture representation. Even
though the classification results are obtained on grayscale images, a direct extension to color-based ones can be straightforward.
Vasileios K. Pothos received the B.Sc. degree in Physics in 2004 and the M.Sc. degree in Electronics and Information Processing in 2006, both from the University of Patras (UoP), Greece. He is currently a Ph.D. candidate in image processing at the Electronics Laboratory in the Department of Physics, UoP, Greece. His main research interests include image processing, pattern recognition and multimedia databases. Dr. Christos Theoharatos received the B.Sc. degree in Physics in 1998, the M.Sc. degree in Electronics and Computer Science in 2001 and the Ph.D. degree in Image Processing and Multimedia Retrieval in 2006, all from the University of Patras (UoP), Greece. He has actively participated in several national research projects and is currently working as a PostDoc researcher at the Electronics Laboratory (ELLAB), Electronics and Computer Division, Department of Physics, UoP. Since the academic year 2002, he has been working as tutor at the degree of lecturer in the Department of Electrical Engineering, of the Technological Institute of Patras. His main research interests include pattern recognition, multimedia databases, image processing and computer vision, data mining and graph theory. Prof. Evangelos Zygouris received the B.Sc. degree in Physics in 1971 and the Ph.D. degree in Digital Filters and Microprocessors in 1984, both from the University of Patras (UoP), Greece. He is currently an Associate Professor at Electronics Laboratory (ELLAB), Department of Physics, UoP, where he teaches at both undergraduate and postgraduate level. He has published papers on digital signal and image processing, digital system design, speech coding systems and real-time processing. His main research interests include digital signal and image processing, DSP system design, micro-controllers, micro-processors and DSPs using VHDL. Prof. George Economou received the B.Sc. degree in Physics from the University of Patras (UoP), Greece in 1976, the M.Sc. degree in Microwaves and Modern Optics from University College London in 1978 and the Ph.D. degree in Fiber Optic Sensor Systems from the University of Patras in 1989. He is currently an Associate Professor at Electronics Laboratory (ELLAB), Department of Physics, UoP, where he teaches at both undergraduate and postgraduate level. He has published papers on non-linear signal and image processing, fuzzy image processing, multimedia databases, data mining and fiber optic sensors. He has also served as referee for many journals, conferences and workshops. His main research interests include signal and image processing, computer vision, pattern recognition and optical signal processing. 相似文献
George EconomouEmail: |
Vasileios K. Pothos received the B.Sc. degree in Physics in 2004 and the M.Sc. degree in Electronics and Information Processing in 2006, both from the University of Patras (UoP), Greece. He is currently a Ph.D. candidate in image processing at the Electronics Laboratory in the Department of Physics, UoP, Greece. His main research interests include image processing, pattern recognition and multimedia databases. Dr. Christos Theoharatos received the B.Sc. degree in Physics in 1998, the M.Sc. degree in Electronics and Computer Science in 2001 and the Ph.D. degree in Image Processing and Multimedia Retrieval in 2006, all from the University of Patras (UoP), Greece. He has actively participated in several national research projects and is currently working as a PostDoc researcher at the Electronics Laboratory (ELLAB), Electronics and Computer Division, Department of Physics, UoP. Since the academic year 2002, he has been working as tutor at the degree of lecturer in the Department of Electrical Engineering, of the Technological Institute of Patras. His main research interests include pattern recognition, multimedia databases, image processing and computer vision, data mining and graph theory. Prof. Evangelos Zygouris received the B.Sc. degree in Physics in 1971 and the Ph.D. degree in Digital Filters and Microprocessors in 1984, both from the University of Patras (UoP), Greece. He is currently an Associate Professor at Electronics Laboratory (ELLAB), Department of Physics, UoP, where he teaches at both undergraduate and postgraduate level. He has published papers on digital signal and image processing, digital system design, speech coding systems and real-time processing. His main research interests include digital signal and image processing, DSP system design, micro-controllers, micro-processors and DSPs using VHDL. Prof. George Economou received the B.Sc. degree in Physics from the University of Patras (UoP), Greece in 1976, the M.Sc. degree in Microwaves and Modern Optics from University College London in 1978 and the Ph.D. degree in Fiber Optic Sensor Systems from the University of Patras in 1989. He is currently an Associate Professor at Electronics Laboratory (ELLAB), Department of Physics, UoP, where he teaches at both undergraduate and postgraduate level. He has published papers on non-linear signal and image processing, fuzzy image processing, multimedia databases, data mining and fiber optic sensors. He has also served as referee for many journals, conferences and workshops. His main research interests include signal and image processing, computer vision, pattern recognition and optical signal processing. 相似文献
9.
Emphysema is a common chronic respiratory disorder characterised by the destruction of lung tissue. It is a progressive disease
where the early stages are characterised by a diffuse appearance of small air spaces, and later stages exhibit large air spaces
called bullae. A bullous region is a sharply demarcated region of emphysema. In this paper, it is shown that an automated
texture-based system based on co-training is capable of achieving multiple levels of emphysema extraction in high-resolution
computed tomography (HRCT) images. Co-training is a semi-supervised technique used to improve classifiers that are trained
with very few labelled examples using a large pool of unseen examples over two disjoint feature sets called views. It is also
shown that examples labelled by experts can be incorporated within the system in an incremental manner. The results are also
compared against “density mask”, currently a standard approach used for emphysema detection in medical image analysis and
other computerized techniques used for classification of emphysema in the literature. The new system can classify diffuse
regions of emphysema starting from a bullous setting. The classifiers built at different iterations also appear to show an
interesting correlation with different levels of emphysema, which deserves more exploration.
Mithun Prasad received his PhD from the University of New South Wales, Sydney, Australia in 2006. He was a postdoctoral scholar at the University of California, Los Angeles and now a research associate at Rensselaer Polytechnic Institute, NY. His research interests are computer aided diagnosis, cell and tissue image analysis. Arcot Sowmya is a Professor, School of Computer Science and Engineering, UNSW, Sydney. She holds a PhD degree in Computer Science from Indian Institute of Technology, Bombay, besides other degrees in Mathematics and Computer Science. Her areas of research include learning in vision as well as embedded system design. Her research has been applied to extraction of linear features in remotely sensed images as well as feature extraction, recognition and computer aided diagnosis in medical images. Peter Wilson is a clinical Radiologist at Pittwater Radiology in Sydney. He was trained at Royal North Shore Hospital and taught Body Imaging at the University of Rochester, NY, prior to taking up his current position. 相似文献
Mithun Prasad (Corresponding author)Email: |
Arcot SowmyaEmail: |
Peter WilsonEmail: |
Mithun Prasad received his PhD from the University of New South Wales, Sydney, Australia in 2006. He was a postdoctoral scholar at the University of California, Los Angeles and now a research associate at Rensselaer Polytechnic Institute, NY. His research interests are computer aided diagnosis, cell and tissue image analysis. Arcot Sowmya is a Professor, School of Computer Science and Engineering, UNSW, Sydney. She holds a PhD degree in Computer Science from Indian Institute of Technology, Bombay, besides other degrees in Mathematics and Computer Science. Her areas of research include learning in vision as well as embedded system design. Her research has been applied to extraction of linear features in remotely sensed images as well as feature extraction, recognition and computer aided diagnosis in medical images. Peter Wilson is a clinical Radiologist at Pittwater Radiology in Sydney. He was trained at Royal North Shore Hospital and taught Body Imaging at the University of Rochester, NY, prior to taking up his current position. 相似文献
10.
Periodicity and stability issues of a <Emphasis Type="Italic">chaotic</Emphasis> pattern recognition neural network 总被引:1,自引:1,他引:0
Traditional pattern recognition (PR) systems work with the model that the object to be recognized is characterized by a set
of features, which are treated as the inputs. In this paper, we propose a new model for PR, namely one that involves chaotic
neural networks (CNNs). To achieve this, we enhance the basic model proposed by Adachi (Neural Netw 10:83–98, 1997), referred to as Adachi’s Neural Network (AdNN), which though dynamic, is not chaotic. We demonstrate that by decreasing the multiplicity of the eigenvalues of the
AdNN’s control system, we can effectively drive the system into chaos. We prove this result here by eigenvalue computations
and the evaluation of the Lyapunov exponent. With this premise, we then show that such a Modified AdNN (M-AdNN) has the desirable
property that it recognizes various input patterns. The way that this PR is achieved is by the system essentially sympathetically “resonating” with a finite periodicity whenever these samples (or their reasonable resemblances) are presented. In this paper, we analyze the M-AdNN for its periodicity, stability
and the length of the transient phase of the retrieval process. The M-AdNN has been tested for Adachi’s dataset and for a
real-life PR problem involving numerals. We believe that this research also opens a host of new research avenues.
Research partially supported by the Natural Sciences and Engineering Research Council of Canada.
Dragos Calitoiu was born in Iasi, Romania on May 7, 1968. He obtained his Electronics degree in 1993 from the Polytechnical University of Bucharest, Romania, and the Ph. D. degree in 2006, from Carleton University, in Ottawa, Canada. He is currently a Postdoctoral Fellow with the Health Policy Research Division of Health Canada. His research interests include Pattern Recognition, Machine Learning, Learning Automata, Chaos Theory and Computational Neuroscience. B. John Oommen was born in Coonoor, India on September 9, 1953. He obtained his B. Tech. degree from the Indian Institute of Technology, Madras, India in 1975. He obtained his M. E. from the Indian Institute of Science in Bangalore, India in 1977. He then went on for his M. S. and Ph. D. which he obtained from Purdue University, in West Lafayettte, Indiana in 1979 and 1982, respectively. He joined the School of Computer Science at Carleton University in Ottawa, Canada, in the 1981–1982 academic year. He is still at Carleton and holds the rank of a Full Professor. His research interests include Automata Learning, Adaptive Data Structures, Statistical and Syntactic Pattern Recognition, Stochastic Algorithms and Partitioning Algorithms. He is the author of more than 260 refereed journal and conference publications and is a Fellow of the IEEE and a Fellow of the IAPR. Dr. Oommen is on the Editorial Board of the IEEE Transactions on Systems, Man and Cybernetics, and Pattern Recognition. Doron Nussbaum received his B.Sc. degree in mathematics and computer science from the University of Tel-Aviv, Israel in 1985, and the M. C. S. and Ph. D. degrees in computer science from Carleton University, Ottawa, Canada in 1988 and 2001, respectively. From 1988 to 1991 he worked for Tydac Technologies as a Manager of Research and Development. His work at Tydac focused on the development of a geographical information system. From 1991 to 1994, he worked for Theratronics as senior software consultant where he worked on the company’s cancer treatment planning software (Theraplan). From 1998 to 2001 he worked for SHL Systemshouse as a senior technical architect. In 2001 he joined the School of Computer Science at Carleton University as an Associate Professor. Dr. Nussbaum’s main research interests are medical computing, computational geometry, robotics and algorithms design. 相似文献
Dragos Calitoiu (Corresponding author)Email: |
B. John OommenEmail: |
Doron NussbaumEmail: |
Dragos Calitoiu was born in Iasi, Romania on May 7, 1968. He obtained his Electronics degree in 1993 from the Polytechnical University of Bucharest, Romania, and the Ph. D. degree in 2006, from Carleton University, in Ottawa, Canada. He is currently a Postdoctoral Fellow with the Health Policy Research Division of Health Canada. His research interests include Pattern Recognition, Machine Learning, Learning Automata, Chaos Theory and Computational Neuroscience. B. John Oommen was born in Coonoor, India on September 9, 1953. He obtained his B. Tech. degree from the Indian Institute of Technology, Madras, India in 1975. He obtained his M. E. from the Indian Institute of Science in Bangalore, India in 1977. He then went on for his M. S. and Ph. D. which he obtained from Purdue University, in West Lafayettte, Indiana in 1979 and 1982, respectively. He joined the School of Computer Science at Carleton University in Ottawa, Canada, in the 1981–1982 academic year. He is still at Carleton and holds the rank of a Full Professor. His research interests include Automata Learning, Adaptive Data Structures, Statistical and Syntactic Pattern Recognition, Stochastic Algorithms and Partitioning Algorithms. He is the author of more than 260 refereed journal and conference publications and is a Fellow of the IEEE and a Fellow of the IAPR. Dr. Oommen is on the Editorial Board of the IEEE Transactions on Systems, Man and Cybernetics, and Pattern Recognition. Doron Nussbaum received his B.Sc. degree in mathematics and computer science from the University of Tel-Aviv, Israel in 1985, and the M. C. S. and Ph. D. degrees in computer science from Carleton University, Ottawa, Canada in 1988 and 2001, respectively. From 1988 to 1991 he worked for Tydac Technologies as a Manager of Research and Development. His work at Tydac focused on the development of a geographical information system. From 1991 to 1994, he worked for Theratronics as senior software consultant where he worked on the company’s cancer treatment planning software (Theraplan). From 1998 to 2001 he worked for SHL Systemshouse as a senior technical architect. In 2001 he joined the School of Computer Science at Carleton University as an Associate Professor. Dr. Nussbaum’s main research interests are medical computing, computational geometry, robotics and algorithms design. 相似文献
11.
We present a probabilistic multiple cause model for the analysis of binary (0–1) data. A distinctive feature of the aspect
Bernoulli (AB) model is its ability to automatically detect and distinguish between “true absences” and “false absences” (both
of which are coded as 0 in the data), and similarly, between “true presences” and “false presences” (both of which are coded
as 1). This is accomplished by specific additive noise components which explicitly account for such non-content bearing causes.
The AB model is thus suitable for noise removal and data explanatory purposes, including omission/addition detection. An important
application of AB that we demonstrate is data-driven reasoning about palaeontological recordings. Additionally, results on
recovering corrupted handwritten digit images and expanding short text documents are also given, and comparisons to other
methods are demonstrated and discussed.
Ella Bingham received her M.Sc. degree in Engineering Physics and Mathematics at Helsinki University of Technology in 1998, and her Dr.Sc. degree in Computer Science at Helsinki University of Technology in 2003. She is currently at Helsinki Institute for Information Technology, located at the University of Helsinki. Her research interests include statistical data analysis and machine learning. Ata Kabán is a lecturer in the School of Computer Science of the University of Birmingham, since 2003. She holds a B.Sc. degree in computer science (1999) from the University “Babes-Bolya” of Cluj-Napoca, Romania, and a Ph.D. in computer science (2001) from the University of Paisley, UK. Her current research interests concern statistical machine learning and data mining. Prior to her career in computer science, she obtained a B.A. degree in musical composition (1994) and the M.A. (1995) and Ph.D. (1999) degrees in musicology from the Music Academy “Gh. Dima” of Cluj-Napoca, Romania. Mikael Fortelius is a palaeontologist with special interest in plant-eating mammals of the Cenozoic, especially ungulates and their relationship with habitat and climate change (the Ungulate Condition). Mikael is Professor of Evolutionary Palaeontology in the Department of Geology and Group Leader in the Institute of Biotechnology (BI), University of Helsinki. Since 1992, he has been engaged in developing a database of Neogene Old World Mammals (). The NOW database is maintained at the Finnish Museum of Natural History and developed in collaboration with an extensive Advisory Board; data access and downloading are entirely public. 相似文献
Mikael ForteliusEmail: |
Ella Bingham received her M.Sc. degree in Engineering Physics and Mathematics at Helsinki University of Technology in 1998, and her Dr.Sc. degree in Computer Science at Helsinki University of Technology in 2003. She is currently at Helsinki Institute for Information Technology, located at the University of Helsinki. Her research interests include statistical data analysis and machine learning. Ata Kabán is a lecturer in the School of Computer Science of the University of Birmingham, since 2003. She holds a B.Sc. degree in computer science (1999) from the University “Babes-Bolya” of Cluj-Napoca, Romania, and a Ph.D. in computer science (2001) from the University of Paisley, UK. Her current research interests concern statistical machine learning and data mining. Prior to her career in computer science, she obtained a B.A. degree in musical composition (1994) and the M.A. (1995) and Ph.D. (1999) degrees in musicology from the Music Academy “Gh. Dima” of Cluj-Napoca, Romania. Mikael Fortelius is a palaeontologist with special interest in plant-eating mammals of the Cenozoic, especially ungulates and their relationship with habitat and climate change (the Ungulate Condition). Mikael is Professor of Evolutionary Palaeontology in the Department of Geology and Group Leader in the Institute of Biotechnology (BI), University of Helsinki. Since 1992, he has been engaged in developing a database of Neogene Old World Mammals (). The NOW database is maintained at the Finnish Museum of Natural History and developed in collaboration with an extensive Advisory Board; data access and downloading are entirely public. 相似文献
12.
Judith L. Klavans Carolyn Sheffield Eileen Abels Jimmy Lin Rebecca Passonneau Tandeep Sidhu Dagobert Soergel 《Multimedia Tools and Applications》2009,42(1):115-138
In this paper, we present a system using computational linguistic techniques to extract metadata for image access. We discuss
the implementation, functionality and evaluation of an image catalogers’ toolkit, developed in the Computational Linguistics
for Metadata Building (CLiMB) research project. We have tested components of the system, including phrase finding for the
art and architecture domain, functional semantic labeling using machine learning, and disambiguation of terms in domain-specific
text vis a vis a rich thesaurus of subject terms, geographic and artist names. We present specific results on disambiguation
techniques and on the nature of the ambiguity problem given the thesaurus, resources, and domain-specific text resource, with
a comparison of domain-general resources and text. Our primary user group for evaluation has been the cataloger expert with
specific expertise in the fields of painting, sculpture, and vernacular and landscape architecture.
Judith L. Klavans is a Senior Research Scientist at the University of Maryland Institute for Advanced Computer Studies (UMIACS), and Principal Investigator on the Mellon-funded Computational Linguistics for Metadata Building (CLiMB) and IMLS-supported T3 research projects. Her research includes text-mining from corpora and dictionaries, disambiguation, and multilingual multidocument summarization. Previously, she directed the Center for Research on Information Access at Columbia University. Carolyn Sheffield holds an M.L.S. from the University of Maryland and her research interests include access issues surrounding visual and time-based materials. She designs, conducts and analyzes the CLiMB user studies and works closely with image catalogers to ensure that the CLiMB system reflects their needs and workflow. Eileen Abels is Masters’ Program Director and Professor in the College of Information Science and Technology at Drexel University. Prior to joining Drexel in January 2007, Dr. Abels spent more than 15 years at the College of Information Studies at the University of Maryland. Her research focuses on user needs and information behaviors. She works with a broad range of information users including translators, business school students and faculty, engineers, scientists, and members of the general public. Dr. Abels holds a PhD from the University of California, Los Angeles. Jimmy Lin’s research interests lie at the intersection of natural language processing and information retrieval. His work integrates knowledge- and data-driven approaches to address users’ information needs. Rebecca J. Passonneau is a Research Scientist at the Center for Computational Learning Systems, Columbia University. Her areas of interest include linking empirical research methods on corpora with computational models of language processing, the intersection of language and context in semantics and pragmatics, corpus design and analysis, and evaluation methods for NLP. Her current projects involve working with machine learning for the Consolidated Edison utility company, and designing an experimental dialog system to take patron book orders by phone for the Andrew Heiskell Braille and Talking Book library. Tandeep Sidhu is the Software Developer and Research Assistant for the CLiMB project. He is incharge of designing the CLiMB Toolkit as well as the NLP modules behind the Toolkit. He is currently pursuing his MS degree in Computer Science. Dagobert Soergel has been teaching information organization at the University of Maryland since 1970 and is an internationally known expert in Knowledge Organization Systems and in Digital Libraries. In the CLiMB project he served as general consultant and was specially involved in the design of study on the relationship between an image and cataloging terms assigned to it. 相似文献
Carolyn SheffieldEmail: |
Judith L. Klavans is a Senior Research Scientist at the University of Maryland Institute for Advanced Computer Studies (UMIACS), and Principal Investigator on the Mellon-funded Computational Linguistics for Metadata Building (CLiMB) and IMLS-supported T3 research projects. Her research includes text-mining from corpora and dictionaries, disambiguation, and multilingual multidocument summarization. Previously, she directed the Center for Research on Information Access at Columbia University. Carolyn Sheffield holds an M.L.S. from the University of Maryland and her research interests include access issues surrounding visual and time-based materials. She designs, conducts and analyzes the CLiMB user studies and works closely with image catalogers to ensure that the CLiMB system reflects their needs and workflow. Eileen Abels is Masters’ Program Director and Professor in the College of Information Science and Technology at Drexel University. Prior to joining Drexel in January 2007, Dr. Abels spent more than 15 years at the College of Information Studies at the University of Maryland. Her research focuses on user needs and information behaviors. She works with a broad range of information users including translators, business school students and faculty, engineers, scientists, and members of the general public. Dr. Abels holds a PhD from the University of California, Los Angeles. Jimmy Lin’s research interests lie at the intersection of natural language processing and information retrieval. His work integrates knowledge- and data-driven approaches to address users’ information needs. Rebecca J. Passonneau is a Research Scientist at the Center for Computational Learning Systems, Columbia University. Her areas of interest include linking empirical research methods on corpora with computational models of language processing, the intersection of language and context in semantics and pragmatics, corpus design and analysis, and evaluation methods for NLP. Her current projects involve working with machine learning for the Consolidated Edison utility company, and designing an experimental dialog system to take patron book orders by phone for the Andrew Heiskell Braille and Talking Book library. Tandeep Sidhu is the Software Developer and Research Assistant for the CLiMB project. He is incharge of designing the CLiMB Toolkit as well as the NLP modules behind the Toolkit. He is currently pursuing his MS degree in Computer Science. Dagobert Soergel has been teaching information organization at the University of Maryland since 1970 and is an internationally known expert in Knowledge Organization Systems and in Digital Libraries. In the CLiMB project he served as general consultant and was specially involved in the design of study on the relationship between an image and cataloging terms assigned to it. 相似文献
13.
Denys Poshyvanyk Andrian Marcus Rudolf Ferenc Tibor Gyimóthy 《Empirical Software Engineering》2009,14(1):5-32
Coupling is an important property of software systems, which directly impacts program comprehension. In addition, the strength
of coupling measured between modules in software is often used as a predictor of external software quality attributes such
as changeability, ripple effects of changes and fault-proneness. This paper presents a new set of coupling measures for Object-Oriented
(OO) software systems measuring conceptual coupling of classes. Conceptual coupling is based on measuring the degree to which
the identifiers and comments from different classes relate to each other. This type of relationship, called conceptual coupling,
is measured through the use of Information Retrieval (IR) techniques. The proposed measures are different from existing coupling
measures and they capture new dimensions of coupling, which are not captured by the existing coupling measures. The paper
investigates the use of the conceptual coupling measures during change impact analysis. The paper reports the findings of
a case study in the source code of the Mozilla web browser, where the conceptual coupling metrics were compared to nine existing
structural coupling metrics and proved to be better predictors for classes impacted by changes.
Denys Poshyvanyk is an Assistant Professor at the College of William and Mary in Virginia. He received his Ph.D. degree in Computer Science from Wayne State University in 2008. He also obtained his MS and MA degrees in Computer Science from the National University of Kyiv-Mohyla Academy, Ukraine and Wayne State University in 2003 and 2006, respectively. His research interests are in software engineering, software maintenance and evolution, program comprehension, reverse engineering, software repository mining, source code analysis and metrics. He is member of the IEEE and ACM. Andrian Marcus is currently an Assistant Professor at the Department of Computer Science at Wayne State University, Detroit. His research interests include software evolution, program understanding, and software visualization, in particular using information retrieval techniques to support software engineering tasks. Since 2005, he has been serving on the steering committee of the IEEE International Conference on Software Maintenance (ICSM) and he will be Program Co-Chair for the 17th IEEE International Conference on Program Comprehension (ICPC 2009) and the 26th IEEE International Conference on Software Maintenance (ICSM 2010). He is the recipient of a Fulbright Junior Research Fellowship in 1997. Rudolf Ferenc is an Assistant Professor at the University of Szeged in Hungary. His research interests include source code analysis, modeling, measurement and design pattern recognition. He is also interested in software quality assurance and open source software development. He is Program Co-Chair of the 13th European Conference on Software Maintenance and Reengineering (CSMR 2009). Tibor Gyimóthy is the head of the Software Engineering Department at the University of Szeged in Hungary. His research interests include program comprehension, slicing, reverse engineering and compiler optimization. He has published over 70 papers in these areas and was the leader of several software engineering R&D projects. He was the Program Co-Chair of the 21th International Conference on Software Maintenance (ICSM 2005). 相似文献
Tibor GyimóthyEmail: |
Denys Poshyvanyk is an Assistant Professor at the College of William and Mary in Virginia. He received his Ph.D. degree in Computer Science from Wayne State University in 2008. He also obtained his MS and MA degrees in Computer Science from the National University of Kyiv-Mohyla Academy, Ukraine and Wayne State University in 2003 and 2006, respectively. His research interests are in software engineering, software maintenance and evolution, program comprehension, reverse engineering, software repository mining, source code analysis and metrics. He is member of the IEEE and ACM. Andrian Marcus is currently an Assistant Professor at the Department of Computer Science at Wayne State University, Detroit. His research interests include software evolution, program understanding, and software visualization, in particular using information retrieval techniques to support software engineering tasks. Since 2005, he has been serving on the steering committee of the IEEE International Conference on Software Maintenance (ICSM) and he will be Program Co-Chair for the 17th IEEE International Conference on Program Comprehension (ICPC 2009) and the 26th IEEE International Conference on Software Maintenance (ICSM 2010). He is the recipient of a Fulbright Junior Research Fellowship in 1997. Rudolf Ferenc is an Assistant Professor at the University of Szeged in Hungary. His research interests include source code analysis, modeling, measurement and design pattern recognition. He is also interested in software quality assurance and open source software development. He is Program Co-Chair of the 13th European Conference on Software Maintenance and Reengineering (CSMR 2009). Tibor Gyimóthy is the head of the Software Engineering Department at the University of Szeged in Hungary. His research interests include program comprehension, slicing, reverse engineering and compiler optimization. He has published over 70 papers in these areas and was the leader of several software engineering R&D projects. He was the Program Co-Chair of the 21th International Conference on Software Maintenance (ICSM 2005). 相似文献
14.
A serial multi-stage classification system for facing the problem of intrusion detection in computer networks is proposed.
The whole decision process is organized into successive stages, each one using a set of features tailored for recognizing
a specific attack category. All the stages employ suitable criteria for estimating the reliability of the performed classification,
so that, in case of uncertainty, information related to a possible attack are only logged for further processing, without
raising an alert for the system manager. This permits to reduce the number of false alarms. On the other hand, in order to
keep low the number of missed detections, the proposed system declares a connection as normal traffic only if all the stages
do not detect an attack. The proposed multi-stage intrusion detection system has been tested on three different services (http, telnet and ftp) of a standard database used for benchmarking intrusion detection systems and also on real network traffic data. The experimental
analysis highlights the effectiveness of the approach: the proposed system behaves significantly better than other multiple
classifier systems performing classification in a single stage.
Luigi Pietro Cordella is a Professor of Computer Science at the Faculty of Engineering of the University of Naples “Federico II” (Italy). He has been Chairman of the Department of Computer Science and Systems and, since 1994, Chairman of the Ph.D. course program in Information Engineering of the University of Naples. His present research interests include Syntactic and Structural Pattern Recognition, Shape Analysis, Document Recognition, OCR, Neural Networks, and Evolutionary Computation. He has published over 150 papers and is editor or co-editor of six books. He is a Fellow of IAPR and a member of IEEE and Computer Society. He has been President of GIRPR (2000–2004), the Italian Association for Pattern Recognition, and member of the Governing Board of the IAPR. Carlo Sansone is Associate Professor of Computer Science at the Faculty of Engineering of the University of Naples “Federico II” (Italy). His research principally focuses on classification techniques, exact and inexact graph matching and multiple-classifier systems theory and applications. He coordinated several projects in the areas of car plate recognition, biomedical images interpretation and network intrusion detection. Prof. Sansone has authored about 90 research papers in international journals and conference proceedings. He serves as referee for many relevant journals in the field of Pattern Recognition and is Associate editor of the Electronic Letters on Computer Vision and Image Analysis journal. He is currently co-editor of a special issue on “Information Fusion in Computer Security” for the Information Fusion journal. 相似文献
Carlo Sansone (Corresponding author)Email: |
Luigi Pietro Cordella is a Professor of Computer Science at the Faculty of Engineering of the University of Naples “Federico II” (Italy). He has been Chairman of the Department of Computer Science and Systems and, since 1994, Chairman of the Ph.D. course program in Information Engineering of the University of Naples. His present research interests include Syntactic and Structural Pattern Recognition, Shape Analysis, Document Recognition, OCR, Neural Networks, and Evolutionary Computation. He has published over 150 papers and is editor or co-editor of six books. He is a Fellow of IAPR and a member of IEEE and Computer Society. He has been President of GIRPR (2000–2004), the Italian Association for Pattern Recognition, and member of the Governing Board of the IAPR. Carlo Sansone is Associate Professor of Computer Science at the Faculty of Engineering of the University of Naples “Federico II” (Italy). His research principally focuses on classification techniques, exact and inexact graph matching and multiple-classifier systems theory and applications. He coordinated several projects in the areas of car plate recognition, biomedical images interpretation and network intrusion detection. Prof. Sansone has authored about 90 research papers in international journals and conference proceedings. He serves as referee for many relevant journals in the field of Pattern Recognition and is Associate editor of the Electronic Letters on Computer Vision and Image Analysis journal. He is currently co-editor of a special issue on “Information Fusion in Computer Security” for the Information Fusion journal. 相似文献
15.
Coupling represents the degree of interdependence between two software components. Understanding software dependency is directly
related to improving software understandability, maintainability, and reusability. In this paper, we analyze the difference
between component coupling and component dependency, introduce a two-parameter component coupling metric and a three-parameter
component dependency metric. An important parameter in both these metrics is coupling distance, which represents the relevance
of two coupled components. These metrics are applicable to layered component-based software. These metrics can be used to
represent the dependencies induced by all types of software coupling. We show how to determine coupling and dependency of
all scales of software components using these metrics. These metrics are then applied to Apache HTTP, an open-source web server.
The study shows that coupling distance is related to the number of modifications of a component, which is an important indicator
of component fault rate, stability and subsequently, component complexity.
Liguo Yu received the Ph.D. degree in Computer Science from Vanderbilt University. He is an assistant professor of Computer and Information Sciences Department at Indiana University South Bend. Before joining IUSB, he was a visiting assistant professor at Tennessee Technological University. His research concentrates on software coupling, software maintenance, software reuse, software testing, software management, and open-source software development. Kai Chen received the Ph.D. degree from the Department of Electrical Engineering and Computer Science at Vanderbilt University. He is working at Google Incorporation. His current research interests include development and maintenance of open-source software, embedded software design, component-based design, model-based design, formal methods and model verification. Srini Ramaswamy earned his Ph.D. degree in Computer Science in 1994 from the Center for Advanced Computer Studies (CACS) at the University of Southwestern Louisiana (now University of Louisiana at Lafayette). His research interests are on intelligent and flexible control systems, behavior modeling, analysis and simulation, software stability and scalability. He is currently the Chairperson of the Department of Computer Science, University of Arkansas at Little Rock. Before joining UALR, he is the chairman of Computer Science Department at Tennessee Tech University. He is member of the Association of Computing Machinery, Society for Computer Simulation International, Computing Professionals for Social Responsibility and a senior member of the IEEE. 相似文献
Srini RamaswamyEmail: Email: |
Liguo Yu received the Ph.D. degree in Computer Science from Vanderbilt University. He is an assistant professor of Computer and Information Sciences Department at Indiana University South Bend. Before joining IUSB, he was a visiting assistant professor at Tennessee Technological University. His research concentrates on software coupling, software maintenance, software reuse, software testing, software management, and open-source software development. Kai Chen received the Ph.D. degree from the Department of Electrical Engineering and Computer Science at Vanderbilt University. He is working at Google Incorporation. His current research interests include development and maintenance of open-source software, embedded software design, component-based design, model-based design, formal methods and model verification. Srini Ramaswamy earned his Ph.D. degree in Computer Science in 1994 from the Center for Advanced Computer Studies (CACS) at the University of Southwestern Louisiana (now University of Louisiana at Lafayette). His research interests are on intelligent and flexible control systems, behavior modeling, analysis and simulation, software stability and scalability. He is currently the Chairperson of the Department of Computer Science, University of Arkansas at Little Rock. Before joining UALR, he is the chairman of Computer Science Department at Tennessee Tech University. He is member of the Association of Computing Machinery, Society for Computer Simulation International, Computing Professionals for Social Responsibility and a senior member of the IEEE. 相似文献
16.
FRCT: fuzzy-rough classification trees 总被引:1,自引:1,他引:0
Using fuzzy-rough hybrids, we have proposed a measure to quantify the functional dependency of decision attribute(s) on condition
attribute(s) within fuzzy data. We have shown that the proposed measure of dependency degree is a generalization of the measure
proposed by Pawlak for crisp data. In this paper, this new measure of dependency degree has been encapsulated into the decision
tree generation mechanism to produce fuzzy-rough classification trees (FRCT); efficient, top-down, multi-class decision tree
structures geared to solving classification problems from feature-based learning examples. The developed FRCT generation algorithm
has been applied to 16 real-world benchmark datasets. It is experimentally compared with the five fuzzy decision tree generation
algorithms reported so far, and the rough decomposition tree algorithm. Comparison has been made in terms of number of rules,
average training time, and classification accuracy. Experimental results show that the proposed algorithm to generate FRCT
outperforms existing fuzzy decision tree generation techniques and rough decomposition tree induction algorithm.
Dr. Rajen Bhatt has obtained his B.E. and M.E. both in Control and Instrumentation, from S.S. Engineering College, Bhavnagar, and from Delhi College of Engineering, New Delhi in 1999 and 2002, respectively. He has obtained his Ph.D. from the Department of Electrical Engineering, Indian Institute of Technology Delhi, INDIA in 2006. He was actively engaged in the development of multimedia course on Control Engineering under the National Program on Technology Enabled Learning (NPTEL). He is a regular reviewer of International Journals like Pattern Recognition, Information Sciences, Pattern Analysis and Applications, and IEEE Trans. on Systems, Man and Cybernatics. Since June 2005, he is working with Imaging team of Samsung India Software Centre as a Lead Engineer. He also serves as a Member of Patent Review Committee at Samsung. He has published several research papers in reputed journals and conferences. His current research interests are Pattern Classification and Regression, Soft Computing, Data mining, Patents and Trademarks, and Information Technology for Education. He holds an expertise over industry standard software project management. Dr. M. Gopal has obtained his B.Tech. (Electrical), M.Tech. (Control systems), and Ph.D. (Control Systems) degrees. all from Birla Institute of Technology and Science, Pilani in 1968, 1970, and 1976, respectively. He has been in the teaching and research field for the last three and half decades; associated with NIT Jaipur, BITS Pilani, IIT Bombay, City University London, and University Technology Malaysia, and IIT Delhi. Since January 1986 he is a Professor with the Electrical Engineering Department, Indian Institute of Technology Delhi. He has published six books in the area of Control Engineering, and a video course on Control Engineering including complete presentation and student questionnaires. He has also published interactive web-compatible multimedia course on Control Engineering, under National Program on Technology Enabled Learning (NPTEL). He has published several research papers in referred journals and conferences. His current research interests include Machine learning, Soft computing technologies, Intelligent control, and e-Learning. 相似文献
Rajen B. BhattEmail: |
Dr. Rajen Bhatt has obtained his B.E. and M.E. both in Control and Instrumentation, from S.S. Engineering College, Bhavnagar, and from Delhi College of Engineering, New Delhi in 1999 and 2002, respectively. He has obtained his Ph.D. from the Department of Electrical Engineering, Indian Institute of Technology Delhi, INDIA in 2006. He was actively engaged in the development of multimedia course on Control Engineering under the National Program on Technology Enabled Learning (NPTEL). He is a regular reviewer of International Journals like Pattern Recognition, Information Sciences, Pattern Analysis and Applications, and IEEE Trans. on Systems, Man and Cybernatics. Since June 2005, he is working with Imaging team of Samsung India Software Centre as a Lead Engineer. He also serves as a Member of Patent Review Committee at Samsung. He has published several research papers in reputed journals and conferences. His current research interests are Pattern Classification and Regression, Soft Computing, Data mining, Patents and Trademarks, and Information Technology for Education. He holds an expertise over industry standard software project management. Dr. M. Gopal has obtained his B.Tech. (Electrical), M.Tech. (Control systems), and Ph.D. (Control Systems) degrees. all from Birla Institute of Technology and Science, Pilani in 1968, 1970, and 1976, respectively. He has been in the teaching and research field for the last three and half decades; associated with NIT Jaipur, BITS Pilani, IIT Bombay, City University London, and University Technology Malaysia, and IIT Delhi. Since January 1986 he is a Professor with the Electrical Engineering Department, Indian Institute of Technology Delhi. He has published six books in the area of Control Engineering, and a video course on Control Engineering including complete presentation and student questionnaires. He has also published interactive web-compatible multimedia course on Control Engineering, under National Program on Technology Enabled Learning (NPTEL). He has published several research papers in referred journals and conferences. His current research interests include Machine learning, Soft computing technologies, Intelligent control, and e-Learning. 相似文献
17.
In this paper, we propose the “Virtual Assistant,” a novel framework for supporting knowledge capturing in videos. The Virtual
Assistant is an artificial agent that simulates a human assistant shown in TV programs and prompts users to provide feedback
by asking questions. This framework ensures that sufficient information is provided in the captured content while users interact
in a natural and enjoyable way with the agent. We developed a prototype agent based on a chatbot-like approach and applied
it to a daily cooking scene. Experimental results demonstrate the potential of the Virtual Assistant framework, as it allows
a person to provide feedback easily with few interruptions and elicits a variety of useful information.
Motoyuki Ozeki received his B.E, M.E. and Ph.D. degrees in engineering from University of Tsukuba, in 2000 and 2005, respectively. He worked as an assistant professor at Kyoto University since 2005. He is currently an assistant professor at Kyoto Institute of Technology. His research interests are in the areas of human-agent interaction and cognitive science. Shunichi Maeda received his B.E and M.E. degrees in electronical engineering from Kyoto University, in 2008. He is currently working in Patent Office (KAJI-SUHARA & ASSOCIATES). Kanako Obata received her B.E. degree in economics from Osaka Prefecture University in2004. She is currently an educational assistant at Kyoto University as since 2004. Her research interests are human-communication and cooking. Yuichi Nakamura received his BE degree in 1985, his ME and PhD degrees in electronical engineering from Kyoto University in 1987 and 1992, respectively. He worked as assistant professor at University of Tsukuba since 1993 and as associate professor since 1999. He is currently a professor at Kyoto University. His research interests and activities include human-computer interactions, video analysis, and video utilization for knowledge sources. 相似文献
Yuichi NakamuraEmail: URL: http://www.ccm.media.kyoto-u.ac.jp/index.php |
Motoyuki Ozeki received his B.E, M.E. and Ph.D. degrees in engineering from University of Tsukuba, in 2000 and 2005, respectively. He worked as an assistant professor at Kyoto University since 2005. He is currently an assistant professor at Kyoto Institute of Technology. His research interests are in the areas of human-agent interaction and cognitive science. Shunichi Maeda received his B.E and M.E. degrees in electronical engineering from Kyoto University, in 2008. He is currently working in Patent Office (KAJI-SUHARA & ASSOCIATES). Kanako Obata received her B.E. degree in economics from Osaka Prefecture University in2004. She is currently an educational assistant at Kyoto University as since 2004. Her research interests are human-communication and cooking. Yuichi Nakamura received his BE degree in 1985, his ME and PhD degrees in electronical engineering from Kyoto University in 1987 and 1992, respectively. He worked as assistant professor at University of Tsukuba since 1993 and as associate professor since 1999. He is currently a professor at Kyoto University. His research interests and activities include human-computer interactions, video analysis, and video utilization for knowledge sources. 相似文献
18.
Quantitatively measuring object-oriented couplings 总被引:1,自引:0,他引:1
One key to several quality factors of software is the way components are connected. Software coupling can be used to estimate
a number of quality factors, including maintainability, complexity, and reliability. Object-oriented languages are designed
to reduce the number of dependencies among classes, which encourages separation of concerns and should reduce the amount of
coupling. At the same time, the object-oriented language features change the way the connections are made, how they must be
analyzed, and how they are measured. This paper discusses software couplings based on object-oriented relationships between
classes, specifically focusing on types of couplings that are not available until after the implementation is completed, and
presents a static analysis tool that measures couplings among classes in Java packages. Data from evaluating the tool on several
open-source projects are provided. The coupling measurement is based on source code, which has the advantage of being quantitative
and more precise than previous measures, but the disadvantage of not being available before implementation, and thus not useful
for some predictive efforts.
Jeff Offutt is Professor of Software Engineering at George Mason University. His current research interests include software testing, analysis of Web applications, object-oriented software, and software maintenance. He has published over 100 refereed research papers and the textbook Introduction to Software Testing (Campbridge University Press, 2008). Offutt is the editor-in-chief of Wiley’s Software Testing, Verification and Reliability journal, and on editorial boards for EmSE, SoSyM, and SQJ. He received the Best Teacher Award from the School of Information Technology and Engineering in 2003. Offutt received a PhD degree from the Georgia Institute of Technology. Aynur Abdurazik received the BEng degree in Computer Engineering from Beijing University of Posts and Telecommunications, Beijing, China, the MS degree in Software Engineering from George Mason University, and the PhD degree in Computer Science from George Mason University. Her research interests are in the area of software engineering, including object-oriented software analysis and testing. Stephen R. Schach is an Associate Professor in the Department of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, Tennessee. Steve is the author of over 130 refereed research papers. He has written 12 software engineering textbooks, including Object-Oriented and Classical Software Engineering, Seventh Edition (McGraw-Hill, 2007). He consults internationally on software engineering topics. Steve’s research interests are in empirical software engineering and open-source software engineering. He obtained his PhD from the University of Cape Town. 相似文献
Stephen R. SchachEmail: |
Jeff Offutt is Professor of Software Engineering at George Mason University. His current research interests include software testing, analysis of Web applications, object-oriented software, and software maintenance. He has published over 100 refereed research papers and the textbook Introduction to Software Testing (Campbridge University Press, 2008). Offutt is the editor-in-chief of Wiley’s Software Testing, Verification and Reliability journal, and on editorial boards for EmSE, SoSyM, and SQJ. He received the Best Teacher Award from the School of Information Technology and Engineering in 2003. Offutt received a PhD degree from the Georgia Institute of Technology. Aynur Abdurazik received the BEng degree in Computer Engineering from Beijing University of Posts and Telecommunications, Beijing, China, the MS degree in Software Engineering from George Mason University, and the PhD degree in Computer Science from George Mason University. Her research interests are in the area of software engineering, including object-oriented software analysis and testing. Stephen R. Schach is an Associate Professor in the Department of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, Tennessee. Steve is the author of over 130 refereed research papers. He has written 12 software engineering textbooks, including Object-Oriented and Classical Software Engineering, Seventh Edition (McGraw-Hill, 2007). He consults internationally on software engineering topics. Steve’s research interests are in empirical software engineering and open-source software engineering. He obtained his PhD from the University of Cape Town. 相似文献
19.
Wan D. Bae Shayma Alkobaisi Seon Ho Kim Sada Narayanappa Cyrus Shahabi 《GeoInformatica》2009,13(4):483-514
As Geographic Information Systems (GIS) technologies have evolved, more and more GIS applications and geospatial data are
available on the web. Spatial objects in a given query range can be retrieved using spatial range query − one of the most
widely used query types in GIS and spatial databases. However, it can be challenging to retrieve these data from various web
applications where access to the data is only possible through restrictive web interfaces that support certain types of queries.
A typical scenario is the existence of numerous business web sites that provide their branch locations through a limited “nearest
location” web interface. For example, a chain restaurant’s web site such as McDonalds can be queried to find some of the closest
locations of its branches to the user’s home address. However, even though the site has the location data of all restaurants
in, for example, the state of California, it is difficult to retrieve the entire data set efficiently due to its restrictive
web interface. Considering that k-Nearest Neighbor (k-NN) search is one of the most popular web interfaces in accessing spatial data on the web, this paper investigates the problem
of retrieving geospatial data from the web for a given spatial range query using only k-NN searches. Based on the classification of k-NN interfaces on the web, we propose a set of range query algorithms to completely cover the rectangular shape of the query
range (completeness) while minimizing the number of k-NN searches as possible (efficiency). We evaluated the efficiency of the proposed algorithms through statistical analysis
and empirical experiments using both synthetic and real data sets.
Wan D. Bae is currently an assistant professor in the Mathematics, Statistics and Computer Science Department at the University of Wisconsin-Stout. She received her Ph.D. in Computer Science from the University of Denver in 2007. Dr. Bae’s current research interests include online query processing, Geographic Information Systems, digital mapping, multidimensional data analysis and data mining in spatial and spatiotemporal databases. Shayma Alkobaisi is currently an assistant professor at the College of Information Technology in the United Arab Emirates University. She received her Ph.D. in Computer Science from the University of Denver in 2008. Dr. Alkobaisi’s research interests include uncertainty management in spatiotemporal databases, online query processing in spatial databases, Geographic Information Systems and computational geometry. Seon Ho Kim is currently an associate professor in the Computer Science & Information Technology Department at the University of District of Columbia. He received his Ph.D. in Computer Science from the University of Southern California in 1999. Dr. Kim’s primary research interests include design and implementation of multimedia storage systems, and databases, spatiotemporal databases, and GIS. He co-chaired the 2004 ACM Workshop on Next Generation Residential Broadband Challenges in conjunction with the ACM Multimedia Conference. Sada Narayanappa is currently an advanced computing technologist at Jeppesen. He received his Ph.D. in Mathematics and Computer Science from the University of Denver in 2006. Dr. Narayanappa’s primary research interests include computational geometry, graph theory, algorithms, design and implementation of databases. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his Ph.D. degree in Computer Science from the University of Southern California in August 1996. Dr. Shahabi’s current research interests include Peer-to-Peer Systems, Streaming Architectures, Geospatial Data Integration and Multidimensional Data Analysis. He is currently on the editorial board of ACM Computers in Entertainment magazine. He is also serving on many conference program committees such as ICDE, SSTD, ACM SIGMOD, ACM GIS. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
Cyrus ShahabiEmail: |
Wan D. Bae is currently an assistant professor in the Mathematics, Statistics and Computer Science Department at the University of Wisconsin-Stout. She received her Ph.D. in Computer Science from the University of Denver in 2007. Dr. Bae’s current research interests include online query processing, Geographic Information Systems, digital mapping, multidimensional data analysis and data mining in spatial and spatiotemporal databases. Shayma Alkobaisi is currently an assistant professor at the College of Information Technology in the United Arab Emirates University. She received her Ph.D. in Computer Science from the University of Denver in 2008. Dr. Alkobaisi’s research interests include uncertainty management in spatiotemporal databases, online query processing in spatial databases, Geographic Information Systems and computational geometry. Seon Ho Kim is currently an associate professor in the Computer Science & Information Technology Department at the University of District of Columbia. He received his Ph.D. in Computer Science from the University of Southern California in 1999. Dr. Kim’s primary research interests include design and implementation of multimedia storage systems, and databases, spatiotemporal databases, and GIS. He co-chaired the 2004 ACM Workshop on Next Generation Residential Broadband Challenges in conjunction with the ACM Multimedia Conference. Sada Narayanappa is currently an advanced computing technologist at Jeppesen. He received his Ph.D. in Mathematics and Computer Science from the University of Denver in 2006. Dr. Narayanappa’s primary research interests include computational geometry, graph theory, algorithms, design and implementation of databases. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his Ph.D. degree in Computer Science from the University of Southern California in August 1996. Dr. Shahabi’s current research interests include Peer-to-Peer Systems, Streaming Architectures, Geospatial Data Integration and Multidimensional Data Analysis. He is currently on the editorial board of ACM Computers in Entertainment magazine. He is also serving on many conference program committees such as ICDE, SSTD, ACM SIGMOD, ACM GIS. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
20.
Fernando Boronat Seguí Juan Carlos Guerri Cebollada Jaime Lloret Mauri 《Multimedia Tools and Applications》2008,40(2):285-319
Most multimedia group and inter-stream synchronization techniques define or use proprietary protocols with new control messages.
Many multimedia applications have been developed using RTP/RTCP as the standard for transmission of multimedia streams over
IP networks. Instead of defining a new protocol, we propose the use of RTP/RTCP to provide synchronization. We take advantage
of the feedback capabilities provided by RTCP and the ability to extend the protocol by extending and creating RTCP messages
containing synchronization information. We have implemented our proposal and tested it in our University WAN. Our experiments
have shown that network load resulting from synchronization is minimized and that asynchronies are within acceptable limits
for multimedia applications.
Dr. Fernando Boronat Seguí was born in Gandia, (Spain) and went to the Polytechnic University of Valencia (UPV) in Spain, where he obtained, in 1993, his M.Sc. in Telecommunications Engineering. In 1994 he worked for a couple of years for Telecommunication Companies before moving back to the UPV in 1996 where he is Lecturer in the Communications Department at the Escuela Politécnica Superior de Gandia. He obtained his PhD degree in 2004 and his topics of interest are Communication networks, Multimedia Systems and Multimedia Synchronization Protocols. He is IEEE member since 1993 and is involved in several IPCs of national and international conferences. Dr. Juan Carlos Guerri Cebollada obtained PhD degree in 1997 and is Lecturer at UPV and he also is the person responsible for the Multimedia Communications Research Group, included in the Instituto de Telecomunicaciones y Aplicaciones Multimedia (iTEAM) at the UPV. He is involved in several IPCs of national and international conferences. Dr. Jaime Lloret Mauri received his M.Sc. in Physics in 1997, his M.Sc. in Electronic Engineering in 2003 at University of Valencia (Spain) and his Ph.D. in telecommunication engineering from the UPV in 2006. He is a Cisco Certified Network Professional Instructor and he also teaches in the EPSG at the UPV. He has been working as a network administrator in several companies. Nowadays he is researching on P2P Networks and on sensor Networks. He is a member of IASTED, and is involved in several IPCs of national and international conferences. 相似文献
Jaime Lloret MauriEmail: |
Dr. Fernando Boronat Seguí was born in Gandia, (Spain) and went to the Polytechnic University of Valencia (UPV) in Spain, where he obtained, in 1993, his M.Sc. in Telecommunications Engineering. In 1994 he worked for a couple of years for Telecommunication Companies before moving back to the UPV in 1996 where he is Lecturer in the Communications Department at the Escuela Politécnica Superior de Gandia. He obtained his PhD degree in 2004 and his topics of interest are Communication networks, Multimedia Systems and Multimedia Synchronization Protocols. He is IEEE member since 1993 and is involved in several IPCs of national and international conferences. Dr. Juan Carlos Guerri Cebollada obtained PhD degree in 1997 and is Lecturer at UPV and he also is the person responsible for the Multimedia Communications Research Group, included in the Instituto de Telecomunicaciones y Aplicaciones Multimedia (iTEAM) at the UPV. He is involved in several IPCs of national and international conferences. Dr. Jaime Lloret Mauri received his M.Sc. in Physics in 1997, his M.Sc. in Electronic Engineering in 2003 at University of Valencia (Spain) and his Ph.D. in telecommunication engineering from the UPV in 2006. He is a Cisco Certified Network Professional Instructor and he also teaches in the EPSG at the UPV. He has been working as a network administrator in several companies. Nowadays he is researching on P2P Networks and on sensor Networks. He is a member of IASTED, and is involved in several IPCs of national and international conferences. 相似文献