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Volumn 2015-November, Issue , 2015, Pages 1841-1844

Wishart RBM based DBN for polarimetric synthetic radar data classification

Author keywords

deep learning; feature learning; polarimetric synthetic radar data; Wishart distribution

Indexed keywords


EID: 84962620507     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2015.7326150     Document Type: Conference Paper
Times cited : (43)

References (12)
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  • 2
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  • 4
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    • Reducing the dimensionality of data with neural networks
    • July
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    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 5
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    • A fast learning algorithm for deep belief nets
    • G. E. Hinton, S. Osindero, Y. W. Teh, "A fast learning algorithm for deep belief nets, " Neural computation, VOL. 18, NO. 7, pp. 1527-1554, 2006.
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    • Welling, M.1    Rosen-Zvi, M.2    Hinton, G.E.3
  • 9
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    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • H. Lee, R. Grosse, R. Ranganath, A. Y. Ng. "Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations". IEEE International Conference. on Machine Learning, pp, 609-616, 2009.
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    • A physical-based unsupervised classification and statistical uncertainties with application to POLSAR imagery
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.