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Volumn 9414, Issue , 2015, Pages

Deep learning with non-medical training used for chest pathology identification

Author keywords

chest X rays; classification; convolutional neural networks; Deep learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER AIDED DIAGNOSIS; CONVOLUTION; DIAGNOSIS; IMAGE RECOGNITION; NEURAL NETWORKS; PATHOLOGY;

EID: 84943754825     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2083124     Document Type: Conference Paper
Times cited : (268)

References (13)
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  • 4
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    • Learning and transferring mid-level image representations using convolutional neural networks
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    • Oquab, M.1    Bottou, L.2    Laptev, I.3    Sivic, J.4
  • 12
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    • A comparative study of texture measures with classification based on featured distributions
    • Ojala, T., Pietikaïnen, M., Harwood, D., "A comparative study of texture measures with classification based on featured distributions," Pattern recognition, 29(1), 51-59, (1996).
    • (1996) Pattern Recognition , vol.29 , Issue.1 , pp. 51-59
    • Ojala, T.1    Pietikaïnen, M.2    Harwood, D.3
  • 13
    • 0035328421 scopus 로고    scopus 로고
    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • Oliva, A., Torralba, A., "Modeling the shape of the scene: A holistic representation of the spatial envelope," International journal of computer vision, 42(3), 145-175, (2001).
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    • Oliva, A.1    Torralba, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.