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Volumn 1, Issue , 2008, Pages 62-67

Image segmentation based on fuzzy hypergraph model

Author keywords

Fuzzy hypergraph model; Image segmentation; Semi supervised learning

Indexed keywords

DIGITAL IMAGE STORAGE; DIGITAL SIGNAL PROCESSING; FEATURE EXTRACTION; FUZZY SETS; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE SEGMENTATION; PATTERN RECOGNITION; PIXELS; WAVELET ANALYSIS; WAVELET TRANSFORMS;

EID: 56749168583     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICWAPR.2008.4635751     Document Type: Conference Paper
Times cited : (1)

References (10)
  • 2
    • 0010805362 scopus 로고    scopus 로고
    • Learning from labeled and unlabeled data using graph mincuts
    • A. Blum, S. Chawla. Learning from labeled and unlabeled data using graph mincuts. ICML, 2001
    • (2001) ICML
    • Blum, A.1    Chawla, S.2
  • 5
    • 56749123289 scopus 로고    scopus 로고
    • L. Grady, G. Funka-Lea. Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials. ECCV, workshop on Computer Vision Approaches to Medical Image Analysis and Mathematical Methods in Biomedical Image Analysis, 2004.
    • L. Grady, G. Funka-Lea. Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials. ECCV, workshop on Computer Vision Approaches to Medical Image Analysis and Mathematical Methods in Biomedical Image Analysis, 2004.
  • 10
    • 33744955193 scopus 로고    scopus 로고
    • Doctoral dissertation. School of Computer Science, Carnegie Mellon University
    • X. Zhu. Semi-supervised learning with graphs. Doctoral dissertation. School of Computer Science, Carnegie Mellon University. 2005.
    • (2005) Semi-supervised learning with graphs
    • Zhu, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.