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Wei Jiang, Alexander Loui, Shih-Fu Chang. Cross-domain learning for semantic concept detection. In TV Content Analysis: Techniques and Applications (CRC Press), Taylor & Francis, 2011.

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In this chapter, we investigate cross-domain learning methods that effectively incorporate information from available training resources in other domains to enhance concept detection in a target domain by considering the domain difference. Our contribution lies in two folds. First, we develop three approaches to incorporate three types of information to assist the target domain: the Cross-Domain Support Vector Machine (CDSVM) algorithm that uses previously learned support vectors; the prediction-based method that uses concept scores of the new data predicted by previously trained concept detectors; and the Adaptive Semi-Supervised SVM (AS3VM) algorithm that incrementally updates previously learned SVM concept detectors to classify new target data. Second, we provide a comprehensive summary and comparative study of the state-of-the-art SVM-based cross-domain learning methods


Wei Jiang
Shih-Fu Chang

BibTex Reference

   Author = {Jiang, Wei and Loui, Alexander and Chang, Shih-Fu},
   Title = {Cross-domain learning for semantic concept detection},
   BookTitle = {TV Content Analysis: Techniques and Applications (CRC Press)},
   Publisher = {Taylor & Francis},
   Year = {2011}

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