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The emergence of Internet of Things (IoT) applications requires intelligence on the edge.
Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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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
Earlier work this paper cites.
https://github.com/tensorflow/models/blob/master/ research/object_detection/data/mscoco_minival_ids.txt
COCO 2014 minival · 2014
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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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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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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size
Forrest N Iandola, Song Han, Matthew W Moskewicz, Khalid Ashraf, William J Dally, and Kurt Keutzer · 2016
Earlier work this paper cites.
Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 2016
Earlier work this paper cites.
Chenzhuo Zhu, Song Han, Huizi Mao, and William J Dally · 2016
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MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, April 2017
A.G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
Cited alongside, same era.
To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu and Suyog Gupta · 2017
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Hello edge: Keyword spotting on microcontrollers
Yundong Zhang, Naveen Suda, Liangzhen Lai, and Vikas Chandra · 2017
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Speed/accuracy trade-offs for modern convolutional object detectors
Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, and Kevin Murphy · 2017
Cited alongside, same era.
Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Netadapt: Platform-aware neural network adaptation for mobile applications
Tien-Ju Yang, Andrew Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, and Hartwig Adam · 2018
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Shufflenet v2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 2018
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Quantizing deep convolutional networks for efficient inference: A whitepaper
Raghuraman Krishnamoorthi · 2018
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Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus
Liangzhen Lai, Naveen Suda, and Vikas Chandra · 2018
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Rethinking machine learning development and deployment for edge devices
Liangzhen Lai and Naveen Suda · 2018
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Cited alongside, same era.
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
B. Jacob, S. Kligys, B. Chen, M. Zhu, M. Tang, A. Howard, H. Adam, and D. Kalenichenko · 2018
Cited alongside, same era.
Speech commands: A dataset for limited-vocabulary speech recognition
Pete Warden · 2018
Cited alongside, same era.
Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, and Quoc V Le · 2018
Cited alongside, same era.
Shufflenet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 2018
Cited alongside, same era.
https://www.nxp.com/support/developer-resources/evaluation-and-development-boards/freedom-development-boards/mcu-boards/freedom-development-platform-for-kinetis-k64-k63-and-k24-mcus
NXP MCUs
Cited in the paper.
https://www.st.com/en/microcontrollers-microprocessors/stm32f7-series.html
STM32F7 Series of MCUs
Cited in the paper.
https://www.st.com/en/evaluation-tools/stm32-nucleo-boards.html
STM32 Nucleo boards
Cited in the paper.
Later among the works it cites.
Not all ops are created equal!
Liangzhen Lai, Naveen Suda, and Vikas Chandra · 2018
Later among the works it cites.
Deterministic binary filters for convolutional neural networks
Vincent W-S Tseng, Sourav Bhattacharya, Javier Fernández Marqués, Milad Alizadeh, Catherine Tong, and Nicholas D Lane · 2018
Later among the works it cites.
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Sparse: Sparse architecture search for cnns on resource-constrained microcontrollers
Igor Fedorov, Ryan P Adams, Matthew Mattina, and Paul N Whatmough · 2019
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