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Volumn , Issue , 2004, Pages 434-440

Probabilistic region relevance learning for content-based image retrieval

Author keywords

Region Importance; Region based Image Retrieval; Relevance Feedback

Indexed keywords

CONTENT-BASED IMAGE RETRIEVAL (CBIR); PROBABILISTIC REGION RELEVANCE LEARNING (PRRL); REGION IMPORTANCE; REGION-BASED IMAGE RETRIEVAL; RELEVANCE FEEDBACK (RF);

EID: 12744260413     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (14)
  • 4
    • 0004067283 scopus 로고
    • Flexible metric nearest neighbor classification
    • Department of Statistics, Standford University
    • J. Friedman. Flexible metric nearest neighbor classification. Technical report, Department of Statistics, Standford University, 1994.
    • (1994) Technical Report
    • Friedman, J.1
  • 5
    • 0018491303 scopus 로고
    • Asymptotically optimum block quantization
    • July
    • A. Gersho. Asymptotically optimum block quantization. IEEE Transactions on Information Theory, IT-25(4):231-262, July 1979.
    • (1979) IEEE Transactions on Information Theory , vol.IT-25 , Issue.4 , pp. 231-262
    • Gersho, A.1
  • 11
    • 0032636367 scopus 로고    scopus 로고
    • Probabilistic feature relevance learning for content-based image retrieval
    • J. Peng, B. Bhanu, and S. Qing. Probabilistic feature relevance learning for content-based image retrieval. Computer Vision and Image Understanding, 75(1/2):150-164, 1999.
    • (1999) Computer Vision and Image Understanding , vol.75 , Issue.1-2 , pp. 150-164
    • Peng, J.1    Bhanu, B.2    Qing, S.3
  • 12


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.