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Volumn 30, Issue 10, 2008, Pages 1866-1871

Graph cuts via ℓ1 norm minimization

Author keywords

Computer vision; Convex optimization; Graph theoretic methods; Linear programming

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; IMAGE PROCESSING; IMAGE SEGMENTATION;

EID: 50249175825     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.82     Document Type: Article
Times cited : (25)

References (20)
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    • Boykov, Y.1    Jolly, M.2
  • 7
    • 0001249888 scopus 로고
    • Block Preconditioning for the Conjugate Gradient Method
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    • Concus, P.1    Golub, G.2    Meurant, G.3
  • 13
    • 34547688865 scopus 로고    scopus 로고
    • An Interior-Point Method for Large-Scale 11 Regularized Logistic Regression
    • July
    • K. Koh, S. Kim, and S. Boyd, "An Interior-Point Method for Large-Scale 11 Regularized Logistic Regression," J. Machine Learning Research vol. 8, pp. 1519-1555, July 2007.
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    • Koh, K.1    Kim, S.2    Boyd, S.3
  • 15
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    • Linear Algebra Operators for GPU Implementation of Numerical Algorithms
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    • Kruger, J.1    Westermann, R.2
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    • Multi-View Reconstruction Using Photo-Consistency and Exact Silhouette Constraints: A Maximum Flow Formulation
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    • Sinha, S.1    Pollefeys, M.2
  • 20
    • 50649084500 scopus 로고    scopus 로고
    • A Seeded Image Segmentation Framework Unifying Graph Cuts and Random Walker which Yields a New Algorithm
    • A.K. Sinop and L. Grady, "A Seeded Image Segmentation Framework Unifying Graph Cuts and Random Walker which Yields a New Algorithm," Proc. 11th Int'l Conf. Computer Vision, pp. 1-8, 2007.
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    • Sinop, A.K.1    Grady, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.