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Support vector machines (SVM) is gaining a considerable attention as an approach to improvement performance of the content-based image retrieval (CBIR). Most SVM for CBIR rely on global feature, which length of the feature representation is fixed. However, region-based image retrieval (RBIR) use variable length representation, and common kernel utilize the inner product or lp norm in input space,...
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if they are likely to belong to the same Flickr groups. Our approach is enabled by a fast Stochastic Intersection Kernel MAchine (SIKMA) training algorithm, which we propose. This proposed training method will be useful for many...
The paper proposes a fuzzy image labeling method that assigns multiple semantic labels together with confidence measures to each region in an image. The confidence measures are derived from the distance of the region to hyperplanes constructed by support vector machines. Test results show that this method yields higher classification accuracy and retrieval precision than crisp labeling methods that...
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