Convolutional neural networks for synthetic aperture radar classification
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[1] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[2] Sergey Ioffe,et al. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning , 2016, AAAI.
[3] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[4] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[6] I. Hajnsek,et al. A tutorial on synthetic aperture radar , 2013, IEEE Geoscience and Remote Sensing Magazine.
[7] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[8] Kazuo Ouchi,et al. Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics , 2013, Remote. Sens..
[9] Dimitri Palaz,et al. Analysis of CNN-based speech recognition system using raw speech as input , 2015, INTERSPEECH.
[10] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[11] Clément Farabet,et al. Torch7: A Matlab-like Environment for Machine Learning , 2011, NIPS 2011.
[12] Keith Woodland. VISION AND LEARNING , 1972 .