We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
Abstract. In this paper, we propose a new method for image classification, in which matrix based kernel features are designed to capture the multiple similarities between images in...
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...