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Volumn 2006, Issue , 2006, Pages 881-886

Fighting the semantic gap on CBIR systems through new relevance feedback techniques

Author keywords

[No Author keywords available]

Indexed keywords

FEEDBACK; ITERATIVE METHODS; QUERY LANGUAGES; SEMANTICS; TEXTURES; USER INTERFACES;

EID: 33845580083     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMS.2006.88     Document Type: Conference Paper
Times cited : (18)

References (10)
  • 4
    • 33751574230 scopus 로고    scopus 로고
    • Learning from negative example in relevance feedback for content-based image retrieval
    • Quebec, Canada, August
    • M. L. Kherfi, D. Ziou, and A. Bernardi:, "Learning from Negative Example in Relevance Feedback for Content-Based Image Retrieval," Proc. International Conference on Pattern Recognition, Quebec, Canada, August, pp. 933-936.
    • Proc. International Conference on Pattern Recognition , pp. 933-936
    • Kherfi, M.L.1    Ziou, D.2    Bernardi, A.3
  • 10
    • 2342504481 scopus 로고    scopus 로고
    • Negative pseudo-relevance feedback in content-based video retrieval
    • Berkeley, CA, November
    • R. Yan, A. G. Hauptmann, and R. Jin, "Negative Pseudo-Relevance Feedback in Content-based Video Retrieval," Proc. ACM Multimedia, Berkeley, CA, November, pp. 343-346.
    • Proc. ACM Multimedia , pp. 343-346
    • Yan, R.1    Hauptmann, A.G.2    Jin, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.