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Learning powerful feature representations with CNNs is hard when training data are limited.
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S. Mallat · 2012
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Scale-space theory in computer vision
T. Lindeberg · 2013
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Rotation, scaling and deformation invariant scattering for texture discrimination
L. Sifre and S. Mallat · 2013
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Detecting brain structural changes as biomarker from magnetic resonance images using a local feature based svm approach
Y. Chen, J. Storrs, L. Tan, L. J. Mazlack, J.-H. Lee, and L. J. Lu · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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Visualizing and understanding convolutional networks
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Learning deep features for scene recognition using places database
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Deep learning
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A. Payan and G. Montana · 2015
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ImageNet Large Scale Visual Recognition Challenge
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