Changbo Yang

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In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning strategy. In this paper, we formulate image annotation as a supervised learning problem under Multiple-Instance Learning (MIL) framework. We present a novel Asymmetrical Support(More)
In an annotated image database, keywords are usually associated with images instead of individual regions, which poses a major challenge for any region based image annotation algorithm. In this paper, we propose to learn the correspondence between image regions and keywords through Multiple-Instance Learning (MIL). After a representative image region has(More)
In this paper, we consider image annotation as a problem of image classification, in which each keyword is treated as a distinct class label. We then build a Bayesian model to solve the classification problem. To preserve the in-variation in the training data and reduce the noises, we also propose to estimate the class conditional probabilities in the(More)
In this paper we present a semantic image retrieval system with integrated feedback mechanism. In our system, we propose a novel feedback solution for semantic retrieval: <i>semantic feedback</i>, which allows our system to interact with users directly at the semantic level. The learning process of the <i>semantic feedback</i> substantially improves the(More)
Learning the semantics of image retrieval using both text and visual information is a challenging research issue in content-based image retrieval systems. In this paper, we present a statistical natural language processing model for image retrieval, which integrates semantic information provided by WordNet, an online lexical reference system, and low-level(More)
and MeSH terms (MeSH Headings). These descriptions are syntactically analyzed and reduced into separate vectors of MeSH terms which are matched against the queries according to Equation 3 (as similarity between expanded and re-weighted vectors). The weights of all MeSH terms are initialized to one while the weights of titles and abstracts are initialized by(More)
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