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We present the next generation of MobileNets based on a combination of complementary search techniques as well as a novel architecture design.
A real-time algorithm for signal analysis with the help of the wavelet transform
Matthias Holschneider, Richard Kronland-Martinet, Jean Morlet, and Ph Tchamitchian · 1989
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Curves and Surfaces in Computer Vision and Graphics
SPSE the Society for Imaging Science, Technology, Society of Photo-optical Instrumentation Engineers, and Technical Association of the Graphic Arts · 1992
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Model compression
Cristian Buciluǎ, Rich Caruana, and Alexandru Niculescu-Mizil · 2006
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
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The pascal visual object classes challenge – a retrospective
Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserma · 2014
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights
Daniel Soudry, Itay Hubara, and Ron Meir · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Semantic image segmentation with deep convolutional nets and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2015
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Binaryconnect: Training deep neural networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre David · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
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Parsenet: Looking wider to see better
Wei Liu, Andrew Rabinovich, and Alexander C. Berg · 2015
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Modeling local and global deformations in deep learning: Epitomic convolution, multiple instance learning, and sliding window detection
George Papandreou, Iasonas Kokkinos, and Pierre-Andre Savalle · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Quantized convolutional neural networks for mobile devices
Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, and Jian Cheng · 2015
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Designing neural network architectures using reinforcement learning
Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar · 2016
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Bridging nonlinearities and stochastic regularizers with gaussian error linear units
Dan Hendrycks and Kevin Gimpel · 2016
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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and <1mb model size
Forrest N. Iandola, Matthew W. Moskewicz, Khalid Ashraf, Song Han, William J. Dally, and Kurt Keutzer · 2016
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Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 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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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le · 2017
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Proxylessnas: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Chamnet: Towards efficient network design through platform-aware model adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, and Niraj K. Jha · 2018
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AMC: automated deep compression and acceleration with reinforcement learning
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Shuchang Zhou, Zekun Ni, Xinyu Zhou, He Wen, Yuxin Wu, and Yuheng Zou · 2016
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V. Le · 2016
Cited alongside, same era.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
Cited alongside, same era.
Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
Cited alongside, same era.
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2017
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
Cited alongside, same era.
Squeeze-and-Excitation Networks
J. Hu, L. Shen, and G. Sun · 2017
Cited alongside, same era.
Condensenet: An efficient densenet using learned group convolutions
Gao Huang, Shichen Liu, Laurens van der Maaten, and Kilian Q. Weinberger · 2017
Cited alongside, same era.
Yihui He and Song Han · 2018
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Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, and Dmitry Kalenichenko · 2018
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Quantizing deep convolutional networks for efficient inference: A whitepaper
Raghuraman Krishnamoorthi · 2018
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DARTS: differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2018
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Espnet: Efficient spatial pyramid of dilated convolutions for semantic segmentation
Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda G. Shapiro, and Hannaneh Hajishirzi · 2018
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Espnetv2: A light-weight, power efficient, and general purpose convolutional neural network
Sachin Mehta, Mohammad Rastegari, Linda G. Shapiro, and Hannaneh Hajishirzi · 2018
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Concentrated-comprehensive convolutions for lightweight semantic segmentation
Hyojin Park, Youngjoon Yoo, Geonseok Seo, Dongyoon Han, Sangdoo Yun, and Nojun Kwak · 2018
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Efficient neural architecture search via parameter sharing
Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, and Jeff Dean · 2018
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Mark Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, and Quoc V. Le · 2018
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Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, and Kurt Keutzer · 2018
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Netadapt: Platform-aware neural network adaptation for mobile applications
Tien-Ju Yang, Andrew G. Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, and Hartwig Adam · 2018
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Semantic segmentation of satellite images using a modified cnn with hard-swish activation function
R. Avenash and P. Vishawanth · 2019
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