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Volumn 10033, Issue , 2016, Pages

Semi-supervised classification of hyperspectral imagery based on stacked autoencoders

Author keywords

Hyperspectral imagery; Image classification; Stacked autoencoders

Indexed keywords

IMAGE PROCESSING; LEARNING SYSTEMS; REMOTE SENSING; SPECTRAL RESOLUTION; SPECTROSCOPY; SUPERVISED LEARNING;

EID: 85000450755     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.2245011     Document Type: Conference Paper
Times cited : (15)

References (10)
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  • 2
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    • Semi-supervised bundle manifold learning for hyperspectral image classification
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    • Li, Z.M.1    Zhang, J.2    Huang, H.3
  • 4
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  • 5
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • G. E. Hinton and R. R. Salakhutdinov, "Reducing the dimensionality of data with neural networks," Science. 313, 504-507, (2006).
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    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 7
    • 79551480483 scopus 로고    scopus 로고
    • Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
    • P. Vincent, H. Larochelle, I. Lajoie, et al, "Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion," Journal of Machine Learning Research. 11, 3371-3408, (2015).
    • (2015) Journal of Machine Learning Research. , vol.11 , pp. 3371-3408
    • Vincent, P.1    Larochelle, H.2    Lajoie, I.3
  • 9
    • 84885023116 scopus 로고    scopus 로고
    • Training restricted Boltzmann machines: An introduction
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    • Fischer, A.1    Igel, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.