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Volumn 3, Issue , 2003, Pages 1792-1795

Learning from user feedback for image retrieval

Author keywords

Contend based image retrieval (CBIR); Expectation maximization (EM); Relevance feedback; User inconsistency; User target model

Indexed keywords

ALGORITHMS; CONTENT BASED RETRIEVAL; FEEDBACK; GAUSSIAN DISTRIBUTION; IMAGE SEGMENTATION; INFORMATION RETRIEVAL; MAXIMUM PRINCIPLE; MULTIMEDIA SIGNAL PROCESSING; SEARCH ENGINES; SEMANTICS; SIGNAL PROCESSING;

EID: 84945893862     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICS.2003.1292775     Document Type: Conference Paper
Times cited : (1)

References (8)
  • 2
    • 0033897023 scopus 로고    scopus 로고
    • The Bayesian image retrieval system, PicHunter: Theory, implementation and psychophysical experiments,"
    • Jan.
    • I. J. Cox, L. Miller, P. Minka, V. Papathomas and P. Yianilos, "The Bayesian image retrieval system, PicHunter: theory, implementation and psychophysical experiments," IEEE Transaction on Image Processing, Vol. 9, No. 1, pp. 20-37, Jan. 2000.
    • (2000) IEEE Transaction on Image Processing , vol.9 , Issue.1 , pp. 20-37
    • Cox, I.J.1    Miller, L.2    Minka, P.3    Papathomas, V.4    Yianilos, P.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.