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In the past few years, video annotation has benefited a lot from the progress of machine learning techniques. Recently, graph-based semi-supervised learning has gained much attention in this domain. However, as a crucial factor of these algorithms, the estimation of pairwise similarity has not been sufficiently studied. Generally, the similarity of two samples is estimated based on the Euclidean distance...
Conventional approaches to automatic image annotation usually suffer from two problems: (1) They cannot guarantee a good semantic coherence of the annotated words for each image, as they treat each word independently without considering the inherent semantic coherence among the words; (2) They heavily rely on visual similarity for judging semantic similarity. To address the above issues, we propose...
The goal of image categorization is to classify a collection of unlabeled images into a set of predefined classes to support semantic-level image retrieval. The distance measures used in most existing approaches either ignored the spatial structures or used them in a separate step. As a result, these distance measures achieved only limited success. To address these difficulties, in this paper, we...
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