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In this paper, we deal with the problem of detecting the existence and the location of salient objects for thumbnail images on which most search engines usually perform visual analysis in order to handle web-scale images. Different from previous techniques, such as sliding windowbased or segmentation-based schemes for detecting salient objects, we propose to use a learning approach, random forest in our solution. Our algorithm exploits global features from multiple saliency information todoi:10.1109/cvpr.2012.6248054 dblp:conf/cvpr/WangWZFZL12 fatcat:e4klofoazjdy5p4nz3zhy7uvyu