Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Transparency in 3D graphics has traditionally been created by ordering the transparent objects from back-to-front with respect to the viewpoint, and rendering the opaque objects ...
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learnin...
Attentive vision is characterized by selective sensing in space and time as well as selective processing with respect to a specic task. Selection in space involves the splitting ...