The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
Abstract. Motivated by image perturbation and the geometry of manifolds, we present a novel method combining these two elements. First, we form a tangent space from a set of pertur...
Abstract. We present a comparative study on how to use discriminative learning methods such as classification, regression, and ranking to address deformable shape segmentation. Tra...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature spac...
This demo presents a graphical user interface and ranking system, coined KSpot, for effectively monitoring the K highest-ranked answers to a query Q in a Wireless Sensor Network. K...