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1.
Julien Ah-Pine Marco Bressan Stephane Clinchant Gabriela Csurka Yves Hoppenot Jean-Michel Renders 《Multimedia Tools and Applications》2009,42(1):31-56
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing
that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media
pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering
them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal
similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity
measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can
frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text
illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications:
a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
Gabriela CsurkaEmail: |
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
2.
Obesity is a multifactorial pathology currently considered one of the main public health problems. Its prevalence is increasing dramatically in the last decades, reaching huge rates in Brazil and many other countries. Regardless of the factors associated with genetic predisposition, this pathology is often associated with abnormal food intake, and also with high consumption of caloric foods and sedentary habits. Thus, obesity is the result of an imbalance between food intake and energy expenditure. One of the greatest research interests in nutrition has currently been the dietetic determinants that may exert an influence on the process of food intake, as well as the role of foods on physiological, physical and chemical factors most related to the processes of satiation and satiety. Based on these aspects, this paper analyzes several research works to gain a better insight of the dietetic factors affecting food intake and body weight regulation. 相似文献
3.
Stéphane Bressan Alfredo Cuzzocrea Panagiotis Karras Xuesong Lu Sadegh Heyrani Nobari 《Journal of Parallel and Distributed Computing》2013
The widespread usage of random graphs has been highlighted in the context of database applications for several years. This because such data structures turn out to be very useful in a large family of database applications ranging from simulation to sampling, from analysis of complex networks to study of randomized algorithms, and so forth. Amongst others, Erd?s–Rényi Γv,p is the most popular model to obtain and manipulate random graphs. Unfortunately, it has been demonstrated that classical algorithms for generating Erd?s–Rényi based random graphs do not scale well in large instances and, in addition to this, fail to make use of the parallel processing capabilities of modern hardware. Inspired by this main motivation, in this paper we propose and experimentally assess a novel parallel algorithm for generating random graphs under the Erd?s–Rényi model that is designed and implemented in a Graphics Processing Unit (GPU), called PPreZER. We demonstrate the nice amenities due to our solution via a succession of several intermediary algorithms, both sequential and parallel, which show the limitations of classical approaches and the benefits due to the PPreZER algorithm. Finally, our comprehensive experimental assessment and analysis brings to light a relevant average speedup gain of PPreZER over baseline algorithms. 相似文献
4.
João Vicente-Neto Maria Cristina Bressan Peter Bitencourt Faria Josye Oliveira e Vieira Maria das Graças Cardoso Maria Beatriz de Abreu Glória Luis Telo da Gama 《Meat science》2010
Chemical composition and fatty acid profiles were determined in Caiman yacare meat originating from the neck and tail cuts of animals raised in the wild (n = 6) or in captivity (n = 6), slaughtered at a live weight of approximately 6 kg. All experimental methods were approved by the appropriate environmental protection agencies. Most chemical components were affected by the origin-cut interaction, with the tail cut of wild animals having the highest amount of intramuscular fat (19.2% of DM) and the lowest of moisture (71.8%) and protein (77.0% of DM). Yacare meat had low amounts of SFA (35.1%), which were similar (P > 0.05) in the cuts and origins studied. The total amount of PUFA was higher (P < 0.05) in wild (31.0%) than in captive animals (23.6%), and n − 3 fatty acids had means of about 5% and 2% for the same groups, respectively (P < 0.05). In general, the FA profile of intramuscular fat in yacare meat had a desirable PUFA/SFA ratio above 0.4. 相似文献
5.
A flexible and efficient technique for the analysis of transmission lines is described. The transmission line is considered as the union of « elementary waveguides », where the medium is uniformly stratified. The modes are determined by matching the field at the interfaces using a procedure that leads to a linear eigenvalue problem involving a limited number of variables. 相似文献
6.
Stefano Sivolella Giulia Brunello Nadia Ferrarese Alessandro Della Puppa Domenico D’Avella Eriberto Bressan Barbara Zavan 《International journal of molecular sciences》2014,15(2):3088-3117
Injury to peripheral nerves can occur as a result of various surgical procedures, including oral and maxillofacial surgery. In the case of nerve transaction, the gold standard treatment is the end-to-end reconnection of the two nerve stumps. When it cannot be performed, the actual strategies consist of the positioning of a nerve graft between the two stumps. Guided nerve regeneration using nano-structured scaffolds is a promising strategy to promote axon regeneration. Biodegradable electrospun conduits composed of aligned nanofibers is a new class of devices used to improve neurite extension and axon outgrowth. Self assembled peptide nanofibrous scaffolds (SAPNSs) demonstrated promising results in animal models for central nervous system injuries, and, more recently, for peripheral nerve injury. Aims of this work are (1) to review electrospun and self-assembled nanofibrous scaffolds use in vitro and in vivo for peripheral nerve regeneration; and (2) its application in peripheral nerve injuries treatment. The review focused on nanofibrous scaffolds with a diameter of less than approximately 250 nm. The conjugation in a nano scale of a natural bioactive factor with a resorbable synthetic or natural material may represent the best compromise providing both biological and mechanical cues for guided nerve regeneration. Injured peripheral nerves, such as trigeminal and facial, may benefit from these treatments. 相似文献
7.
K Zhu-Salzman RE Shade H Koiwa RA Salzman M Narasimhan RA Bressan PM Hasegawa LL Murdock 《Canadian Metallurgical Quarterly》1998,95(25):15123-15128
Griffonia simplicifolia leaf lectin II (GSII), a plant defense protein against certain insects, consists of an N-acetylglucosamine (GlcNAc)-binding large subunit with a small subunit having sequence homology to class III chitinases. Much of the insecticidal activity of GSII is attributable to the large lectin subunit, because bacterially expressed recombinant large subunit (rGSII) inhibited growth and development of the cowpea bruchid, Callosobruchus maculatus (F). Site-specific mutations were introduced into rGSII to generate proteins with altered GlcNAc binding, and the different rGSII proteins were evaluated for insecticidal activity when added to the diet of the cowpea bruchid. At pH 5.5, close to the physiological pH of the cowpea bruchid midgut lumen, rGSII recombinant proteins were categorized as having high (rGSII, rGSII-Y134F, and rGSII-N196D mutant proteins), low (rGSII-N136D), or no (rGSII-D88N, rGSII-Y134G, rGSII-Y134D, and rGSII-N136Q) GlcNAc-binding activity. Insecticidal activity of the recombinant proteins correlated with their GlcNAc-binding activity. Furthermore, insecticidal activity correlated with the resistance to proteolytic degradation by cowpea bruchid midgut extracts and with GlcNAc-specific binding to the insect digestive tract. Together, these results establish that insecticidal activity of GSII is functionally linked to carbohydrate binding, presumably to the midgut epithelium or the peritrophic matrix, and to biochemical stability of the protein to digestive proteolysis. 相似文献
8.
Elizabethe Adriana Esteves Hércia Stampini Duarte Martino Fernanda Cristina Esteves Oliveira Josefina Bressan Neuza Maria Brunoro Costa 《Food chemistry》2010
The nutrient, phytic acid, oxalate, trypsin inhibitors and isoflavones composition of a whole soy flour produced from a new cultivar (UFV-116), lacking lipoxygenases 2 and 3, compared to a conventional cultivar (OCEPAR-19) were determined. Protein and dietary fibres (total, soluble and insoluble) were similar for both cultivars. OCEPAR-19 was higher in lipids and UFV-116 in ash content (p < 0.05). Indispensable, dispensable and total aminoacid as well as Ca, K and Mg were higher for UFV-116. This cultivar also showed higher levels of phytic acid, oxalate and trypsin inhibitors (p < 0.05). Total saturated and unsaturated fatty acids were similar between them. However, palmitic and linoleic acids were higher for UFV-116 and stearic, α-linolenic and oleic acids for OCEPAR-19 (p < 0.05). The higher concentration of isoflavones in UFV-116 (p < 0.05) could provide better benefit for human health. Experimental studies are necessary to evaluate health effects of this new soybean cultivar. 相似文献
9.
Alejandro S. Cruces Pablo Lopez‐Crespo Stefano Bressan Takamoto Itoh 《Fatigue & Fracture of Engineering Materials & Structures》2019,42(8):1633-1645
In this work, the multiaxial behaviour of 316 stainless steel is studied under the lens of critical plane approach. A series of experiments were developed on dog bone–shaped hollow cylindrical specimens made of type 316 stainless steel. Five different loading conditions were assessed with (a) only tensile axial stress, (b) only hoop stress, (c) combination of axial and hoop stresses with square shape, (d) combination of tensile axial and hoop stresses with L shape, and (e) combination of compressive axial and hoop stresses with L shape. The fatigue analysis is performed with four different critical plane theories, namely, Wang‐Brown, Fatemi‐Socie, Liu I, and Liu II. The efficiency of all four theories is studied in terms of the accuracy of their life predictions and crack failure plane angle. The best fatigue life predictions were obtained with Liu II model, and the best predictions of the failure plane were obtained with Liu I model. 相似文献
10.