-
1
-
-
85007493861
-
A tutorial on synthetic aperture radar
-
Moreira A, Iraola P, Younis M, et al. A tutorial on synthetic aperture radar [J]. IEEE Geoscience and Remote Sensing Magazine, 2013, 1(1): 6-43
-
(2013)
IEEE Geoscience and Remote Sensing Magazine
, vol.1
, Issue.1
, pp. 6-43
-
-
Moreira, A.1
Iraola, P.2
Younis, M.3
-
2
-
-
0142009643
-
Optimum model-based segmentation techniques for multifrequency polarimetric SAR images of urban areas
-
Lombardo P, Sciotti M, Pellizzeri T M, et al. Optimum model-based segmentation techniques for multifrequency polarimetric SAR images of urban areas [J]. IEEE Trans on Geoscience and Remote Sensing, 2003, 41(9): 1959-1975
-
(2003)
, vol.41
, Issue.9
, pp. 1959-1975
-
-
Lombardo, P.1
Sciotti, M.2
Pellizzeri, T.M.3
-
3
-
-
34548359491
-
A study of land cover classification using polarimetric SAR parameters
-
Alberga V. A study of land cover classification using polarimetric SAR parameters [J]. Int Journal of Remote Sensing, 2007, 28(17): 3851-3870
-
(2007)
, vol.28
, Issue.17
, pp. 3851-3870
-
-
Alberga, V.1
-
4
-
-
34548420140
-
A method for calibrated maximum likelihood classification of forest types
-
Hagner O, Reese H. A method for calibrated maximum likelihood classification of forest types [J]. Remote Sensing of Environment, 2007, 110(4): 438-444
-
(2007)
Remote Sensing of Environment
, vol.110
, Issue.4
, pp. 438-444
-
-
Hagner, O.1
Reese, H.2
-
5
-
-
63249104262
-
Unsupervised classification of polarimetric SAR images by EM algorithm
-
Khan K U, Yang J, Zhang W. Unsupervised classification of polarimetric SAR images by EM algorithm [J]. IEICE Trans on Communications, 2007, E90-B(12): 3632-3642
-
(2007)
, vol.E90-B
, Issue.12
, pp. 3632-3642
-
-
Khan, K.U.1
Yang, J.2
Zhang, W.3
-
6
-
-
0026678254
-
Classification of multispectral remote sensing data using a back-propagation neural network
-
Heermann P, Khazenie N. Classification of multispectral remote sensing data using a back-propagation neural network [J]. IEEE Trans on Geoscience and Remote Sensing, 1992, 30(1): 81-88
-
(1992)
, vol.30
, Issue.1
, pp. 81-88
-
-
Heermann, P.1
Khazenie, N.2
-
7
-
-
0141569007
-
An assessment of the effectiveness of decision tree methods for land cover classification
-
Pal M, Mather P M. An assessment of the effectiveness of decision tree methods for land cover classification [J]. Remote Sensing of Environment, 2003, 86(4): 1145-1161
-
(2003)
Remote Sensing of Environment
, vol.86
, Issue.4
, pp. 1145-1161
-
-
Pal, M.1
Mather, P.M.2
-
8
-
-
70549111594
-
Support vector machine for multifrequency SAR polarimetric data classification
-
Lardeux C, Frison P, Tison C, et al. Support vector machine for multifrequency SAR polarimetric data classification [J]. IEEE Trans on Geoscience and Remote Sensing, 2009, 47(12): 4143-4152
-
(2009)
, vol.47
, Issue.12
, pp. 4143-4152
-
-
Lardeux, C.1
Frison, P.2
Tison, C.3
-
9
-
-
84868092003
-
Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach
-
Niu X, Ban Y F. Multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using an object-based support vector machine and a rule-based approach [J]. Int Journal of Remote Sensing, 2013, 34(1): 1-26
-
(2013)
, vol.34
, Issue.1
, pp. 1-26
-
-
Niu, X.1
Ban, Y.F.2
-
10
-
-
84883156337
-
A novel contextual classification algorithm for multitemporal polarimetric SAR data
-
Niu X, Ban Y F. A novel contextual classification algorithm for multitemporal polarimetric SAR data [J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(3): 681-685
-
(2014)
IEEE Geoscience and Remote Sensing Letters
, vol.11
, Issue.3
, pp. 681-685
-
-
Niu, X.1
Ban, Y.F.2
-
11
-
-
33746600649
-
Reducing the dimensionality of data with neural networks
-
Hinton G E, Salakhutdinov R. Reducing the dimensionality of data with neural networks [J]. Science, 2006, 313(5786): 504-507
-
(2006)
Science
, vol.313
, Issue.5786
, pp. 504-507
-
-
Hinton, G.E.1
Salakhutdinov, R.2
-
12
-
-
85032782045
-
Deep learning and its applications to signal and information processing
-
Yu D, Deng L. Deep learning and its applications to signal and information processing [J]. IEEE Signal Processing Magazine, 2011, 28(1): 145-154
-
(2011)
IEEE Signal Processing Magazine
, vol.28
, Issue.1
, pp. 145-154
-
-
Yu, D.1
Deng, L.2
-
13
-
-
77958488310
-
Deep machine learning-A new frontier in artificial intelligence
-
Arel I, Rose C, Karnowski T. Deep machine learning-A new frontier in artificial intelligence [J]. IEEE Computational Intelligence Magazine, 2010, 5(4): 13-18
-
(2010)
IEEE Computational Intelligence Magazine
, vol.5
, Issue.4
, pp. 13-18
-
-
Arel, I.1
Rose, C.2
Karnowski, T.3
-
15
-
-
84879854889
-
Representation learning: A review and new perspectives
-
Bengio Y, Courville A, Vincent P. Representation learning: A review and new perspectives [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2013, 35(8): 1798-1828
-
(2013)
, vol.35
, Issue.8
, pp. 1798-1828
-
-
Bengio, Y.1
Courville, A.2
Vincent, P.3
-
16
-
-
85015872485
-
Deep learning comes of age
-
Anthes G. Deep learning comes of age [J]. Communications of the ACM, 2013, 56(6): 13-15
-
(2013)
Communications of the ACM
, vol.56
, Issue.6
, pp. 13-15
-
-
Anthes, G.1
-
17
-
-
84892142922
-
The learning machines
-
Jones N. The learning machines [J]. Nature, 2014, 505(7482): 146-148
-
(2014)
Nature
, vol.505
, Issue.7482
, pp. 146-148
-
-
Jones, N.1
-
18
-
-
84908017576
-
Deep learning: New hotspot in machine learning
-
in Chinese
-
Hu Xiaolin, Zhu Jun. Deep learning: New hotspot in machine learning [J]. Communications of the CCF, 2013, 9(7): 64-69 (in Chinese)
-
(2013)
Communications of the CCF
, vol.9
, Issue.7
, pp. 64-69
-
-
Hu, X.1
Zhu, J.2
-
19
-
-
84885069866
-
Deep learning: Yesterday, today, and tomorrow
-
in Chinese
-
Yu Kai, Jia Lei, Chen Yuqiang, et al. Deep learning: Yesterday, today, and tomorrow [J]. Journal of Computer Research and Development, 2013, 50(9): 1799-1804 (in Chinese)
-
(2013)
Journal of Computer Research and Development
, vol.50
, Issue.9
, pp. 1799-1804
-
-
Yu, K.1
Jia, L.2
Chen, Y.3
-
20
-
-
78149333575
-
Learning to detect roads in high resolution aerial images
-
Piscataway, NJ: IEEE
-
Mnih V, Hinton G E. Learning to detect roads in high resolution aerial images [C] //Proc of 2010 European Conf Computer Vision (ECCV2010). Piscataway, NJ: IEEE, 2010: 210-223
-
(2010)
, pp. 210-223
-
-
Mnih, V.1
Hinton, G.E.2
-
21
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
Hinton G E, Osindero S, Teh Y. A fast learning algorithm for deep belief nets [J]. Neural Computation, 2006, 18(7): 1527-1554
-
(2006)
Neural Computation
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.3
-
22
-
-
0013344078
-
Training products of experts by minimizing contrastive divergence
-
Hinton G E. Training products of experts by minimizing contrastive divergence [J]. Neural Computation, 2002, 14(8): 1771-1800
-
(2002)
Neural Computation
, vol.14
, Issue.8
, pp. 1771-1800
-
-
Hinton, G.E.1
-
24
-
-
78650474133
-
A practical guide to training restricted Boltzmann machines, UTML TR 2010-003
-
Toronto: Department of Computer Science, University of Toronto
-
Hinton G E. A practical guide to training restricted Boltzmann machines, UTML TR 2010-003 [R]. Toronto: Department of Computer Science, University of Toronto, 2010
-
(2010)
-
-
Hinton, G.E.1
-
25
-
-
45749110924
-
Representational power of restricted Boltzmann machines and deep belief networks
-
Roux N, Bengio Y. Representational power of restricted Boltzmann machines and deep belief networks [J]. Neural Computation, 2008, 20(7): 1631-1649
-
(2008)
Neural Computation
, vol.20
, Issue.7
, pp. 1631-1649
-
-
Roux, N.1
Bengio, Y.2
-
26
-
-
59449087310
-
Exploring strategies for training deep neural networks
-
Larochelle H, Begnio Y, Louradour J, et al. Exploring strategies for training deep neural networks [J]. Journal of Machine Learning Research, 2009, 10(1): 1-40
-
(2009)
Journal of Machine Learning Research
, vol.10
, Issue.1
, pp. 1-40
-
-
Larochelle, H.1
Begnio, Y.2
Louradour, J.3
-
27
-
-
84865560594
-
LIBSVM: A library for support vector machines
-
Lin C J. LIBSVM: A library for support vector machines [OL]. [2013-11-12]. http://www.csie.ntu.edu.tw/~cjlin/libsvm/
-
(2013)
-
-
Lin, C.J.1
|