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Recent research on deep neural networks has focused primarily on improving accuracy.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B.Boser, J.S. Denker, D. Henderson, R.E. Howard, W. Hubbard, and L.D. Jackel · 1989
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Evolving neural networks through augmenting topologies
K.O. Stanley and R. Miikkulainen · 2002
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An optimization methodology for neural network weights and architectures
T.B. Ludermir, A. Yamazaki, and C. Zanchettin · 2006
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ImageNet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E. Hinton · 2010
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Torch7: A matlab-like environment for machine learning
Ronan Collobert, Koray Kavukcuoglu, and Clement Farabet · 2011
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An optimization methodology for neural network weights and architectures
J. Bergstra and Y. Bengio · 2012
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ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Practical bayesian optimization of machine learning algorithms
J. Snoek, H. Larochelle, and R.P. Adams · 2012
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Decaf: A deep convolutional activation feature for generic visual recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2013
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Min Lin, Qiang Chen, and Shuicheng Yan · 2013
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Deformable part descriptors for fine-grained recognition and attribute prediction
Ning Zhang, Ryan Farrell, Forrest Iandola, and Trevor Darrell · 2013
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cuDNN: efficient primitives for deep learning
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer · 2014
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Exploiting linear structure within convolutional networks for efficient evaluation
E.L Denton, W. Zaremba, J. Bruna, Y. LeCun, and R. Fergus · 2014
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Densenet: Implementing efficient convnet descriptor pyramids
Forrest N. Iandola, Matthew W. Moskewicz, Sergey Karayev, Ross B. Girshick, Trevor Darrell, and Kurt Keutzer · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Cited alongside, same era.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Shallow networks for high-accuracy road object-detection
Khalid Ashraf, Bichen Wu, Forrest N. Iandola, Matthew W. Moskewicz, and Kurt Keutzer · 2016
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A implementation of squeezenet in chainer
Eddie Bell · 2016
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Keras: Deep learning library for theano and tensorflow
Francois Chollet · 2016
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Tesla’s new autopilot: Better but still needs improvement
Consumer Reports · 2016
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Distributed deep learning using synchronous stochastic gradient descent
Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, and Pradeep Dubey · 2016
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Squeezenet keras implementation
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Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2014
Cited alongside, same era.
SegNet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2015
Cited alongside, same era.
From captions to visual concepts and back
Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh Srivastava, Li Deng, Piotr Dollar, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C. Platt, C. Lawrence Zitnick, and Geoffrey Zweig · 2015
Cited alongside, same era.
Deformable part models are convolutional neural networks
Ross B. Girshick, Forrest N. Iandola, Trevor Darrell, and Jitendra Malik · 2015
Cited alongside, same era.
Convolutional neural networks at constrained time cost
Kaiming He and Jian Sun · 2015
Cited alongside, same era.
DeepLogo: Hitting logo recognition with the deep neural network hammer
Forrest N. Iandola, Anting Shen, Peter Gao, and Kurt Keutzer · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Cited alongside, same era.
Highway networks
R. K. Srivastava, K. Greff, and J. Schmidhuber · 2015
Cited alongside, same era.
DT42 · 2016
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Zynqnet: An fpga-accelerated embedded convolutional neural network
David Gschwend · 2016
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Ristretto: Hardware-oriented approximation of convolutional neural networks
Philipp Gysel · 2016
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convert squeezenet to mxnet
Guo Haria · 2016
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FireCaffe: near-linear acceleration of deep neural network training on compute clusters
Forrest N. Iandola, Khalid Ashraf, Matthew W. Moskewicz, and Kurt Keutzer · 2016
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Systematic evaluation of cnn advances on the imagenet
Dmytro Mishkin, Nikolay Sergievskiy, and Jiri Matas · 2016
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Going deeper with embedded fpga platform for convolutional neural network
Jiantao Qiu, Jie Wang, Song Yao, Kaiyuan Guo, Boxun Li, Erjin Zhou, Jincheng Yu, Tianqi Tang, Ningyi Xu, Sen Song, Yu Wang, and Huazhong Yang · 2016
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Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, and Vincent Vanhoucke · 2016
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FireModule.lua
Sagar M Waghmare · 2016
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