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      Canonical correlation analysis: an overview with application to learning methods.

      1 , ,
      Neural computation
      MIT Press - Journals

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          Abstract

          We present a general method using kernel canonical correlation analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments, we look at two approaches of retrieving images based on only their content from a text query. We compare orthogonalization approaches against a standard cross-representation retrieval technique known as the generalized vector space model.

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          Author and article information

          Journal
          Neural Comput
          Neural computation
          MIT Press - Journals
          0899-7667
          0899-7667
          Dec 2004
          : 16
          : 12
          Affiliations
          [1 ] School of Electronics and Computer Science, Image, Speech and Intelligent Systems Research Group, University of Southampton, Southampton S017 1BJ, UK. drh@ecs.soton.ac.uk
          Article
          10.1162/0899766042321814
          15516276
          4308be00-6f47-4a90-ab84-7a2e70ac858a
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