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81.
82.
Ying YuAuthor Vitae Bin WangAuthor Vitae Liming ZhangAuthor Vitae 《Neurocomputing》2011,74(11):2008-2017
This paper proposes a bottom-up attention model based on pulsed Hebbian neural networks. The salience of the visual input can be generated through the networks using a simple normalization process, which can be calculated rapidly. Moreover, visual salience in this model can be represented as binary codes that mimic neuronal pulses in the human brain. Experimental results on psychophysical patterns and eye fixation prediction for natural images prove the effectiveness and efficiency of the model. In an arduous task of detecting ships in synthetic aperture radar (SAR) images, there are large amounts of data to be processed in real time. As a fast and effective technique for saliency detection, the proposed model is applied to ship detection in SAR images and its robustness against speckles is further proved. 相似文献
83.
M. CastroAuthor Vitae B. KumarAuthor VitaeJ.F. FellerAuthor Vitae Z. HaddiAuthor VitaeA. AmariAuthor Vitae B. BouchikhiAuthor Vitae 《Sensors and actuators. B, Chemical》2011,159(1):213-219
We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters. 相似文献
84.
We present a novel mesh denoising and smoothing method in this paper. Our approach starts by estimating the principal curvatures
and mesh saliency value for each vertex. Then, we calculate the uniform principal curvature of each vertex based on the weighted
average of local principal curvatures. After that, we use the weighted bi-quadratic Bézier surface to fit the neighborhood
of each vertex using the least-square method and obtain the new vertex position by adjusting the parameters of the fitting
surface. Experiments show that our smoothing method preserves the geometric feature of the original mesh model efficiently.
Our approach also prevents the volume shrinkage of the input mesh and obtains smooth boundaries for non-closed mesh models. 相似文献
85.
Ramsey F. Hamade Mohamad Y. Jaber Sverker Sikstrm 《Computers & Industrial Engineering》2009,56(4):1510-1518
Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested. 相似文献
86.
Fethallah Benmansour Laurent D. Cohen 《Journal of Mathematical Imaging and Vision》2009,33(2):209-221
In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal
path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically
using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the
topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain
visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal
paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving
extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar
idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to
3D data with promising results.
相似文献
Laurent D. CohenEmail: |
87.
88.
89.
文章提出基于稀疏PCA的多阶次分数阶傅里叶变换(fractional Fourier features,Frft)特征的人脸识别(Multiple Order discrete fractional Fourier Features ,MOFF). 鉴于分数阶傅里叶变换对光照、表情的鲁棒性, 并已在图像处理领域得到应用,首先,Frft幅度随阶次的变换呈现压缩性,而SPCA提取其主要信息将且分为主要信息域和次要信息域,融合二者的互补信息组成混合幅度特征,然后融合混合幅度特征、实部特征和虚部特征,最后融合不同阶次下Frft域特征。此外该文提出基于贪婪算法的分数阶阶次选择算法和基于Fisherfaces的权重方法。ORL 和AR人脸数据库上的仿真证明了本算法的有效性。 相似文献
90.
针对稀疏保持投影算法在特征提取过程中无监督和L1范数优化的计算量较大的问题,提出一种基于流形学习和稀疏约束的快速特征提取算法。首先通过逐类PCA构造级联字典,并基于该字典通过最小二乘法快速学习稀疏保持结构;其次构造用于描述不同子流形距离的局部类间散度函数;然后整合所学习到的稀疏表示信息和局部类间散度信息以达到既考虑判别效率又保持稀疏表示结构的目的;所提算法最终转化为一个求解广义特征值问题。在公共人脸数据库(Yale,ORL和Extended Yale B)中 的 测试结果验证了该方法的可行性和有效性。 相似文献