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In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks.
Rectified linear units improve restricted boltzmann machines
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Rectifier nonlinearities improve neural network acoustic models
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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J. S. Ren, L. Xu, Q. Yan, and W. Sun · 2015
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Instance normalization: The missing ingredient for fast stylization. arxiv 2016
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High-resolution image inpainting using multi-scale neural patch synthesis
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Pyramid scene parsing network
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2017
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Encoder-decoder with atrous separable convolution for semantic image segmentation
L.-C. Chen, Y. Zhu, G. Papandreou, F. Schroff, and H. Adam · 2018
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