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Volumn , Issue , 2008, Pages 3204-3207

Learning distance metric for semi-supervised image segmentation

Author keywords

Distance metric learning; Image segmentation; Semi supervised

Indexed keywords

DISTANCE METRIC LEARNING; DISTANCE METRICS; FUNGAL DISEASE; GRADIENT DESCENT METHOD; GRAPH-BASED; GRAPH-BASED METHODS; IMAGE APPEARANCE; IMAGE PROCESSING APPLICATIONS; LOCAL OPTIMUM SOLUTION; OPTIMIZATION PROBLEMS; PARAMETER SELECTION; RESEARCH AREAS; SEMI-SUPERVISED; STEADY PERFORMANCE; USER ANNOTATIONS;

EID: 69949169161     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2008.4712477     Document Type: Conference Paper
Times cited : (9)

References (13)
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  • 2
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    • Boykov, Y.1    Veksler, O.2    Zabih, R.3
  • 3
    • 33845581508 scopus 로고    scopus 로고
    • Active Graph Cuts
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    • (2006) CVPR , vol.1 , pp. 1023-1029
    • Juan, O.1    Boykov, Y.2
  • 4
    • 33745890914 scopus 로고    scopus 로고
    • Effciently Solving Dynamic Markov Random Fields Using Graph Cuts
    • P. Kohli and PHS Torr, "Effciently Solving Dynamic Markov Random Fields Using Graph Cuts," ICCV, vol. 2, 2005.
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  • 5
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    • Semi-Supervised Classification Using Linear Neighborhood Propagation
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    • (2006) CVPR
    • Wang, F.1    Wang, J.2    Zhang, C.3    Shen, H.C.4
  • 9
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    • Interactive Image Segmentation via Adaptive Weighted Distances
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    • Protiere, A.1    Sapiro, G.2
  • 10
    • 84879571292 scopus 로고    scopus 로고
    • Distance metric learning, with application to clustering with side-information
    • E.P. Xing, A.Y. Ng, M.I. Jordan, and S. Russell, "Distance metric learning, with application to clustering with side-information," NIPS, vol. 15, pp. 505-512, 2003.
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    • Xing, E.P.1    Ng, A.Y.2    Jordan, M.I.3    Russell, S.4
  • 11
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    • A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
    • D. Martin, C. Fowlkes, D. Tal, and J. Malik, "A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics," ICCV, vol. 2, pp. 416-423, 2001.
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  • 12
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    • Learning to detect natural image boundaries using local brightness, color, and texture cues
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.