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Using Dual Cascading Learning Frameworks for Image Indexing (2004)  (Make Corrections)  
Joo-Hwee Lim, Jesse S. Jin



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Abstract: To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intra-image and inter-class semantics for image indexing and retrieval. In the supervised learning version, support vector detectors... (Update)

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BibTeX entry:   (Update)

@misc{ lim-using,
  author = "Joo-Hwee Lim and Jesse S. Jin",
  title = "Using Dual Cascading Learning Frameworks for Image Indexing",
  url = "citeseer.ist.psu.edu/lim04using.html" }
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