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Recent years have produced great advances in training large, deep neural networks (DNNs), including notable successes in training convolutional neural networks (convnets) to recognize natural images.
Statistics of natural image categories
Torralba, Antonio and Oliva, Aude · 2003
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Deng, Jia, Dong, Wei, Socher, Richard, Li, Li-Jia, Li, Kai, and Fei-Fei, Li · 2009
Earlier work this paper cites.
Visualizing higher-layer features of a deep network
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, and Vincent, Pascal · 2009
Earlier work this paper cites.
Theano: a CPU and GPU math expression compiler
Bergstra, James, Breuleux, Olivier, Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Desjardins, Guillaume, Turian, Joseph, Warde-Farley, David, and Bengio, Yoshua · 2010
Earlier work this paper cites.
Torch7: A matlab-like environment for machine learning
Collobert, Ronan, Kavukcuoglu, Koray, and Farabet, Clément · 2011
Earlier work this paper cites.
Deep sparse rectifier networks
Glorot, Xavier, Bordes, Antoine, and Bengio, Yoshua · 2011
Earlier work this paper cites.
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E, Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoff · 2012
Earlier work this paper cites.
Pylearn2: a machine learning research library
Goodfellow, Ian J, Warde-Farley, David, Lamblin, Pascal, Dumoulin, Vincent, Mirza, Mehdi, Pascanu, Razvan, Bergstra, James, Bastien, Frédéric, and Bengio, Yoshua · 2013
Cited alongside, same era.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, Karen, Vedaldi, Andrea, and Zisserman, Andrew · 2013
Cited alongside, same era.
Intriguing properties of neural networks
Szegedy, Christian, Zaremba, Wojciech, Sutskever, Ilya, Bruna, Joan, Erhan, Dumitru, Goodfellow, Ian J., and Fergus, Rob · 2013
Cited alongside, same era.
Visualizing and understanding convolutional neural networks
Zeiler, Matthew D and Fergus, Rob · 2013
Cited alongside, same era.
Explaining and Harnessing Adversarial Examples
Understanding Deep Image Representations by Inverting Them
Mahendran, A. and Vedaldi, A · 2014
Later among the works it cites.
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Nguyen, Anh, Yosinski, Jason, and Clune, Jeff · 2014
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Deepface: Closing the gap to human-level performance in face verification
Taigman, Yaniv, Yang, Ming, Ranzato, Marc’Aurelio, and Wolf, Lior · 2014
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How transferable are features in deep neural networks?
Yosinski, J., Clune, J., Bengio, Y., and Lipson, H · 2014
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Object detectors emerge in deep scene cnns
Zhou, Bolei, Khosla, Aditya, Lapedriza, Àgata, Oliva, Aude, and Torralba, Antonio · 2014
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Goodfellow, Ian J, Shlens, Jonathon, and Szegedy, Christian · 2014
Cited alongside, same era.
Deep Speech: Scaling up end-to-end speech recognition
Hannun, A., Case, C., Casper, J., Catanzaro, B., Diamos, G., Elsen, E., Prenger, R., Satheesh, S., Sengupta, S., Coates, A., and Ng, A. Y · 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.
Microsoft COCO: common objects in context
Lin, Tsung-Yi, Maire, Michael, Belongie, Serge, Hays, James, Perona, Pietro, Ramanan, Deva, Dollár, Piotr, and Zitnick, C. Lawrence · 2014
Cited alongside, same era.
Dai, Jifeng, Lu, Yang, and Wu, Ying Nian · 2015
Closest in time.
FaceNet: A Unified Embedding for Face Recognition and Clustering
Schroff, F., Kalenichenko, D., and Philbin, J · 2015
Closest in time.