Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
For character recognition in document analysis, some classes are closely overlapped but are not necessarily to be separated before contextual information is exploited. For classifi...
We propose a new discriminant analysis using composite vectors for eye detection. A composite vector consists of a number of pixels inside a window on an image. The covariance of ...
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
In this paper, we present a novel approach to solving the supervised dimensionality reduction problem by encoding an image object as a general tensor of 2nd or higher order. First...
Shuicheng Yan, Dong Xu, Qiang Yang, Lei Zhang, Xia...