Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
Existing built-in self test (BIST) strategies require the use of specialized test pattern generation hardware which introduces signicant area overhead and performance degradation...
This paper delves into the problem of face recognition using color as an important cue in improving the accuracy of recognition. To perform recognition of color images, we use the...
We consider the problem of segmenting multiple rigid motions from point correspondences in multiple affine views. We cast this problem as a subspace clustering problem in which th...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analy...