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Volumn 8675 LNCS, Issue PART 3, 2014, Pages 369-376

Scalable histopathological image analysis via active learning

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS;

EID: 84906985867     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10443-0_47     Document Type: Conference Paper
Times cited : (19)

References (17)
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  • 2
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  • 3
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    • Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features
    • Doyle, S., Agner, S., Madabhushi, A., Feldman, M., Tomaszewski, J.: Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features. In: Proc. ISBI (2008)
    • Proc. ISBI (2008)
    • Doyle, S.1    Agner, S.2    Madabhushi, A.3    Feldman, M.4    Tomaszewski, J.5
  • 5
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    • An analysis of approximations for maximizing submodular set functions-ii
    • Fisher, M.L., Nemhauser, G.L., Wolsey, L.A.: An analysis of approximations for maximizing submodular set functions-ii. In: Polyhedral Combinatorics pp. 73-87 (1978)
    • (1978) Polyhedral Combinatorics , pp. 73-87
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  • 6
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    • Imageminer: A software system for comparative analysis of tissue microarrays using content-based image retrieval, high-performance computing, and grid technology
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  • 8
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    • Golovin, D., Krause, A.: Adaptive submodularity: Theory and applications in active learning and stochastic optimization. JAIR 42(1), 427-486 (2011)
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    • Golovin, D.1    Krause, A.2
  • 10
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    • Batch mode active learning and its application to medical image classification
    • Hoi, S.C., Jin, R., Zhu, J., Lyu, M.R.: Batch mode active learning and its application to medical image classification. In: Proc. ICML (2006)
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    • Hoi, S.C.1    Jin, R.2    Zhu, J.3    Lyu, M.R.4
  • 11
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.