A lazy processing approach to user relevance feedback for content-based image retrieval

Proceedings - 2010 IEEE International Symposium on Multimedia, ISM 2010

Volumn , Issue , 2010, Pages 342-346

  Nilpanich, Sirikunya ^a   Hua, Kien A ^a   Petkova, Antoniya ^a   Ho, Yao H ^b  

^a University of Central Florida   (United States)

^b INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

Content based image retrieval; Machine learning; Relevance feedback

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CONTENT BASED IMAGE RETRIEVAL; DATA CLUSTERING; EXPERIMENTAL STUDIES; FEATURE DIMENSIONS; KERNEL MACHINE; LEARNING COSTS; LEARNING METHODS; LOCAL CLASSIFIER; MACHINE-LEARNING; NEGATIVE FEEDBACK; OVERFITTING; POSITIVE FEEDBACK; PROCESSING APPROACH; RANDOM SAMPLING; RELEVANCE FEEDBACK; SUBSTANTIAL DELAYS; TRAINING SETS; USER FEEDBACK; USER RELEVANCE FEEDBACKS;

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; CLUSTERING ALGORITHMS; CONTENT BASED RETRIEVAL; LEARNING SYSTEMS; NEURAL NETWORKS;

FEEDBACK;

EID: 79951755954     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISM.2010.58     Document Type: Conference Paper

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