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Volumn , Issue , 2016, Pages 744-751

DeepBE: Learning Deep Binary Encoding for Multi-label Classification

Author keywords

[No Author keywords available]

Indexed keywords

BINS; CLASSIFICATION (OF INFORMATION); COMPUTER VISION; ENCODING (SYMBOLS); IMAGE RECOGNITION; MEAN SQUARE ERROR;

EID: 85010204798     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2016.98     Document Type: Conference Paper
Times cited : (24)

References (24)
  • 1
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    • 83155175374 scopus 로고    scopus 로고
    • Classifier chains for multi-label classification
    • J. Read, B. Pfahringer, G. Holmes, and E. Frank. Classifier chains for multi-label classification. Machine learning, 85(3):333-359, 2011
    • (2011) Machine Learning , vol.85 , Issue.3 , pp. 333-359
    • Read, J.1    Pfahringer, B.2    Holmes, G.3    Frank, E.4
  • 15
    • 0033905095 scopus 로고    scopus 로고
    • Boostexter: A boosting-based system for text categorization
    • R. E. Schapire and Y. Singer. Boostexter: A boosting-based system for text categorization. Machine learning, 39(2):135-168, 2000
    • (2000) Machine Learning , vol.39 , Issue.2 , pp. 135-168
    • Schapire, R.E.1    Singer, Y.2
  • 16
    • 85083953063 scopus 로고    scopus 로고
    • Very deep convolutional networks for large-scale image recognition
    • K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. ICLR, 2015
    • (2015) ICLR
    • Simonyan, K.1    Zisserman, A.2
  • 20
    • 84933515061 scopus 로고    scopus 로고
    • Multi-label classification: An overview
    • Aristotle University of Thessaloniki, Greece
    • G. Tsoumakas and I. Katakis. Multi-label classification: An overview. Dept. of Informatics, Aristotle University of Thessaloniki, Greece, 2006
    • (2006) Dept. of Informatics
    • Tsoumakas, G.1    Katakis, I.2
  • 21
    • 38049123909 scopus 로고    scopus 로고
    • Random k-labelsets: An ensemble method for multilabel classification
    • Springer
    • G. Tsoumakas and I. Vlahavas. Random k-labelsets: An ensemble method for multilabel classification. In Machine learning: ECML 2007, pages 406-417. Springer, 2007
    • (2007) Machine Learning: ECML 2007 , pp. 406-417
    • Tsoumakas, G.1    Vlahavas, I.2
  • 24
    • 33947681316 scopus 로고    scopus 로고
    • Ml-knn: A lazy learning approach to multi-label learning
    • M.-L. Zhang and Z.-H. Zhou. Ml-knn: A lazy learning approach to multi-label learning. Pattern recognition, 40(7):2038-2048, 2007.
    • (2007) Pattern Recognition , vol.40 , Issue.7 , pp. 2038-2048
    • Zhang, M.-L.1    Zhou, Z.-H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.