articleSep 29, 2007Closed access

Cross-domain video concept detection using adaptive svms

Carnegie Mellon University · IBM (United States)

Indexed incrossref

Abstract

Many multimedia applications can benefit from techniques for adapting existing classifiers to data with different distributions. One example is cross-domain video concept detection which aims to adapt concept classifiers across various video domains. In this paper, we explore two key problems for classifier adaptation: (1) how to transform existing classifier(s) into an effective classifier for a new dataset that only has a limited number of labeled examples, and (2) how to select the best existing classifier(s) for adaptation. For the first problem, we propose Adaptive Support Vector Machines (A-SVMs) as a general method to adapt one or more existing classifiers of any type to the new dataset. It aims to…

Citation impact

700
total citations
FWCI
25.15
Percentile
100%
References
18
Citations per year

Authors

3

Topics & keywords

Keywords
  • Classifier (UML)
  • Computer science
  • Support vector machine
  • Domain adaptation
  • Artificial intelligence
  • Margin classifier
  • Machine learning
  • Pattern recognition (psychology)
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