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Volumn 1, Issue , 2012, Pages 567-574

Learning to label aerial images from noisy data

Author keywords

[No Author keywords available]

Indexed keywords

AERIAL IMAGES; LABEL IMAGES; LABELED TRAINING DATA; LOSS FUNCTIONS; NOISY DATA;

EID: 84867136367     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (412)

References (16)
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    • 84863400534 scopus 로고    scopus 로고
    • Learning hybrid models for image annotation with partially labeled data
    • He, Xuming and Zemel, Richard S. Learning hybrid models for image annotation with partially labeled data. In NIPS, pp. 625-632, 2008.
    • (2008) NIPS , pp. 625-632
    • He, X.1    Zemel, R.S.2
  • 4
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • July
    • Hinton, Geoffrey E., Osindero, Simon, and Teh, Yee-Whye. A fast learning algorithm for deep belief nets. Neural Comput, 18:1527-1554, July 2006.
    • (2006) Neural Comput , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 6
    • 77953219772 scopus 로고    scopus 로고
    • Semantic classification by covariance descriptors within a randomized forest
    • IEEE
    • Kluckner, Stefan and Bischof, Horst. Semantic classification by covariance descriptors within a randomized forest. In Computer Vision Workshops (ICCV), pp. 665-672. IEEE, 2009.
    • (2009) Computer Vision Workshops (ICCV) , pp. 665-672
    • Kluckner, S.1    Bischof, H.2
  • 7
    • 78650439909 scopus 로고    scopus 로고
    • Semantic classification in aerial imagery by integrating appearance and height information
    • ACCV, Springer
    • Kluckner, Stefan, Mauthner, Thomas, Roth, Peter M., and Bischof, Horst. Semantic classification in aerial imagery by integrating appearance and height information. In ACCV, volume 5995 of Lecture Notes in Computer Science, pp. 477-488. Springer, 2009.
    • (2009) Lecture Notes in Computer Science , vol.5995 , pp. 477-488
    • Kluckner, S.1    Mauthner, T.2    Roth, P.M.3    Bischof, H.4
  • 10
    • 39749187303 scopus 로고    scopus 로고
    • Object extraction in photogrammetric computer vision
    • March
    • Mayer, Helmut. Object extraction in photogrammetric computer vision. ISPRS Journal of Photogrammetry and Remote Sensing, 63(2):213-222, March 2008.
    • (2008) ISPRS Journal of Photogrammetry and Remote Sensing , vol.63 , Issue.2 , pp. 213-222
    • Mayer, H.1
  • 11
    • 78149337911 scopus 로고    scopus 로고
    • Technical Report UTML TR 2009-004, Department of Computer Science, University of Toronto, November
    • Mnih, Volodymyr. Cudamat: a CUDA-based matrix class for python. Technical Report UTML TR 2009-004, Department of Computer Science, University of Toronto, November 2009.
    • (2009) Cudamat: A CUDA-based Matrix Class for Python
    • Mnih, V.1
  • 13
    • 77956509090 scopus 로고    scopus 로고
    • Rectified linear units improve restricted boltzmann machines
    • Nair, Vinod and Hinton, Geoffrey E. Rectified linear units improve restricted boltzmann machines. In ICML, pp. 807-814, 2010.
    • (2010) ICML , pp. 807-814
    • Nair, V.1    Hinton, G.E.2
  • 15
    • 80053455455 scopus 로고    scopus 로고
    • Technical Report UTML TR 2010-002, University of Toronto, Department of Computer Science
    • Tieleman, T. Gnumpy: an easy way to use GPU boards in Python. Technical Report UTML TR 2010-002, University of Toronto, Department of Computer Science, 2010.
    • (2010) Gnumpy: An Easy Way to Use GPU Boards in Python
    • Tieleman, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.