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Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs).
The mnist database of handwritten digits, 1998
LeCun, Yann, Cortes, Corinna, and Burges, Christopher JC · 1998
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Dimensionality reduction by learning an invariant mapping
Hadsell, Raia, Chopra, Sumit, and LeCun, Yann · 2006
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
Huang, Gary B, Ramesh, Manu, Berg, Tamara, and Learned-Miller, Erik · 2007
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What is the best multi-stage architecture for object recognition?
Jarrett, Kevin, Kavukcuoglu, Koray, Ranzato, Marc’Aurelio, and LeCun, Yann · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, Alex · 2009
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Rectified linear units improve restricted boltzmann machines
Nair, Vinod and Hinton, Geoffrey E · 2010
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Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E, Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E · 2012
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Goodfellow, Ian J, Warde-Farley, David, Mirza, Mehdi, Courville, Aaron, and Bengio, Yoshua · 2013
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Regularization of neural networks using dropconnect
Wan, Li, Zeiler, Matthew, Zhang, Sixin, Cun, Yann L, and Fergus, Rob · 2013
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Stochastic pooling for regularization of deep convolutional neural networks
Zeiler, Matthew D and Fergus, Rob · 2013
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Incremental face alignment in the wild
Asthana, Akshay, Zafeiriou, Stefanos, Cheng, Shiyang, and Pantic, Maja · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Jia, Yangqing, Shelhamer, Evan, Donahue, Jeff, Karayev, Sergey, Long, Jonathan, Girshick, Ross, Guadarrama, Sergio, and Darrell, Trevor · 2014
Cited alongside, same era.
Network in network
Lin, Min, Chen, Qiang, and Yan, Shuicheng · 2014
Cited alongside, same era.
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, et al · 2014
Cited alongside, same era.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Sermanet, Pierre, Eigen, David, Zhang, Xiang, Mathieu, Michaël, Fergus, Rob, and LeCun, Yann · 2014
Cited alongside, same era.
Robust face recognition via multimodal deep face representation
Ding, Changxing and Tao, Dacheng · 2015
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, Sergey and Szegedy, Christian · 2015
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Deeply-supervised nets
Lee, Chen-Yu, Xie, Saining, Gallagher, Patrick, Zhang, Zhengyou, and Tu, Zhuowen · 2015
Later among the works it cites.
Recurrent convolutional neural network for object recognition
Liang, Ming and Hu, Xiaolin · 2015
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Deep face recognition
Parkhi, Omkar M, Vedaldi, Andrea, and Zisserman, Andrew · 2015
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Fitnets: Hints for thin deep nets
Romero, Adriana, Ballas, Nicolas, Kahou, Samira Ebrahimi, Chassang, Antoine, Gatta, Carlo, and Bengio, Yoshua · 2015
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Simonyan, Karen and Zisserman, Andrew · 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.
Deep networks with internal selective attention through feedback connections
Stollenga, Marijn F, Masci, Jonathan, Gomez, Faustino, and Schmidhuber, Jürgen · 2014
Cited alongside, same era.
Deep learning face representation by joint identification-verification
Sun, Yi, Chen, Yuheng, Wang, Xiaogang, and Tang, Xiaoou · 2014
Cited alongside, same era.
Deepface: Closing the gap to human-level performance in face verification
Taigman, Yaniv, Yang, Ming, Ranzato, Marc’Aurelio, and Wolf, Lars · 2014
Cited alongside, same era.
Learning face representation from scratch
Yi, Dong, Lei, Zhen, Liao, Shengcai, and Li, Stan Z · 2014
Cited alongside, same era.
Deep residual learning for image recognition
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian
Cited in the paper.
Facenet: A unified embedding for face recognition and clustering
Schroff, Florian, Kalenichenko, Dmitry, and Philbin, James · 2015
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Striving for simplicity
Springenberg, Jost Tobias, Dosovitskiy, Alexey, Brox, Thomas, and Riedmiller, Martin · 2015
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Deeply learned face representations are sparse, selective, and robust
Sun, Yi, Wang, Xiaogang, and Tang, Xiaoou · 2015
Later among the works it cites.
Going deeper with convolutions
Szegedy, Christian, Liu, Wei, Jia, Yangqing, Sermanet, Pierre, Reed, Scott, Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, and Rabinovich, Andrew · 2015
Later among the works it cites.
Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree
Lee, Chen-Yu, Gallagher, Patrick W, and Tu, Zhuowen · 2016
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