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In this paper we investigate the performance of different types of rectified activation functions in convolutional neural network: standard rectified linear unit (ReLU), leaky rectified linear unit (Leaky ReLU), parametric rectified linear unit (PReLU) and a new randomized leaky rectified linear units (RReLU).
Learning multiple layers of features from tiny images
Krizhevsky, Alex and Hinton, Geoffrey · 2009
Earlier work this paper cites.
Rectified linear units improve restricted Boltzmann machines
Nair, Vinod and Hinton, Geoffrey E · 2010
Earlier work this paper cites.
Deep sparse rectifier networks
Glorot, Xavier, Bordes, Antoine, and Bengio, Yoshua · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E · 2012
Earlier work this paper cites.
Lin, Min, Chen, Qiang, and Yan, Shuicheng · 2013
Earlier work this paper cites.
Rectifier nonlinearities improve neural network acoustic models
Maas, Andrew L, Hannun, Awni Y, and Ng, Andrew Y · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
Girshick, Ross, Donahue, Jeff, Darrell, Trevor, and Malik, Jitendra · 2014
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Spatial pyramid pooling in deep convolutional networks for visual recognition
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian · 2014
Cited alongside, same era.
Dropout: A simple way to prevent neural networks from overfitting
Srivastava, Nitish, Hinton, Geoffrey, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan · 2014
Cited alongside, same era.
Deeply learned face representations are sparse, selective, and robust
Sun, Yi, Wang, Xiaogang, and Tang, Xiaoou · 2014
Cited alongside, same era.
Going deeper with convolutions
Szegedy, Christian, Liu, Wei, Jia, Yangqing, Sermanet, Pierre, Reed, Scott, Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, and Rabinovich, Andrew · 2014
Later among the works it cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, Sergey and Szegedy, Christian · 2015
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, Olga, Deng, Jia, Su, Hao, Krause, Jonathan, Satheesh, Sanjeev, Ma, Sean, Huang, Zhiheng, Karpathy, Andrej, Khosla, Aditya, Bernstein, Michael, Berg, Alexander C., and Fei-Fei, Li · 2015
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Transferring rich feature hierarchies for robust visual tracking
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Wang, Naiyan, Li, Siyi, Gupta, Abhinav, and Yeung, Dit-Yan · 2015
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