Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Fault-tolerant distributed real-time systems are presently facing a lot of new challenges. Although many techniques provide effective masking of node failures on the architectural...
An online feature evaluation method for visual
object tracking is put forward in this paper. Firstly, a
combined feature set is built using color histogram (HC)
bins and gradien...
We propose an efficient method to recognize multi-stroke handwritten symbols. The method is based on computing the truncated Legendre-Sobolev expansions of the coordinate functio...
To develop effective learning algorithms for online cursive word recognition is still a challenge research issue. In this paper, we propose a probabilistic framework to model the ...