This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
We present a new framework for data hiding in images printed with clustered dot halftones. Our application scenario, like other hardcopy embedding methods, encounters fundamental c...
Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysi...
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han, Thoma...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Effective use of the memory hierarchy is critical for achieving high performance on embedded systems. We focus on the class of streaming applications, which is increasingly preval...
Janis Sermulins, William Thies, Rodric M. Rabbah, ...