SVM or deep learning? A comparative study on remote sensing image classification-Reference-Cited by-同舟云学术

SVM or deep learning? A comparative study on remote sensing image classification

Published:2016-07-12 Issue:23 Volume:21 Page:7053-7065
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Liu Peng,Choo Kim-Kwang Raymond,Wang Lizhe,Huang Fang

Funder

National Natural Science Foundation of China (CN)

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s00500-016-2247-2/fulltext.html

Reference34 articles.

1. Bengio Yoshua, Lamblin Pascal, Popovici Dan, Larochelle Hugo (2007) Greedy layer-wise training of deep networks. Adv Neural Inf Process Syst 19:153

2. Burges Christopher JC (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov 2(2):121–167

3. Chen S, Wang H, Xu F, Jin YQ (2016) Target classification using the deep convolutional networks for sar images. IEEE Trans Geosci Remote Sens 54(8):4806–4817

4. Ciodaro T, Deva D, De Seixas JM and Damazio D (2012) Online particle detection with neural networks based on topological calorimetry information. In: Journal of physics: conference series, vol 368, p 012–030. IOP Publishing

5. Collobert Ronan, Weston Jason, Bottou Léon, Karlen Michael, Kavukcuoglu Koray, Kuksa Pavel (2011) Natural language processing (almost) from scratch. J Mach Learn Res 12:2493–2537

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