The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Chemical expressions have more variant structures in 2-D space than that in math equations. In this paper we propose a unified framework for recognizing handwritten chemical expre...
Image summarization is to determine a smaller but faithful representation of the original visual content. In this paper, we propose a context saliency based image summarization ap...
Liang Shi, Jinqiao Wang, Lei Xu, Hanqing Lu, Chang...
To gain a deeper understanding of the impact of spatial embedding on the dynamics of complex systems we employ a measure of interaction complexity developed within neuroscience us...
Christopher L. Buckley, Seth Bullock, Lionel Barne...
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. This paper introduces a new hierarchical ...
Silvia Valero, Philippe Salembier, Jocelyn Chanuss...