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Exploration of Automatic Mixed-Precision Search for Deep Neural Networks
2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
◽
10.1109/aicas.2019.8771498
◽
2019
◽
Author(s):
Xuyang Guo
◽
Yuanjun Huang
◽
Hsin-pai Cheng
◽
Bing Li
◽
Wei Wen
◽
...
Keyword(s):
Neural Networks
◽
Deep Neural Networks
◽
Mixed Precision
Download Full-text
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Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages
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10.1145/3394450.3397468
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2020
◽
Author(s):
Ruizhe Zhao
◽
Wayne Luk
◽
Chao Xiong
◽
Xinyu Niu
◽
Kuen Hung Tsoi
Keyword(s):
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Mixed-precision architecture based on computational memory for training deep neural networks
2018 IEEE International Symposium on Circuits and Systems (ISCAS)
◽
10.1109/iscas.2018.8351656
◽
2018
◽
Cited By ~ 22
Author(s):
S. R. Nandakumar
◽
Manuel Le Gallo
◽
Irem Boybat
◽
Bipin Rajendran
◽
Abu Sebastian
◽
...
Keyword(s):
Neural Networks
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Deep Neural Networks
◽
Mixed Precision
◽
Computational Memory
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Applying Lightweight Soft Error Mitigation Techniques to Embedded Mixed Precision Deep Neural Networks
IEEE Transactions on Circuits and Systems I Regular Papers
◽
10.1109/tcsi.2021.3097981
◽
2021
◽
pp. 1-11
Author(s):
Geancarlo Abich
◽
Jonas Gava
◽
Rafael Garibotti
◽
Ricardo Reis
◽
Luciano Ost
Keyword(s):
Neural Networks
◽
Deep Neural Networks
◽
Soft Error
◽
Error Mitigation
◽
Mixed Precision
◽
Mitigation Techniques
◽
Soft Error Mitigation
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Research on Mixed-Precision Quantization and Fault-Tolerant of Deep Neural Networks
10.1145/3487075.3487135
◽
2021
◽
Author(s):
Zhaoxin Wang
◽
Jing Wang
◽
Kun Qian
Keyword(s):
Neural Networks
◽
Deep Neural Networks
◽
Fault Tolerant
◽
Mixed Precision
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Deep neural networks trained with heavier data augmentation learn features closer to representations in hIT
10.32470/ccn.2018.1046-0
◽
2018
◽
Cited By ~ 1
Author(s):
Alex Hernández-García
◽
Johannes Mehrer
◽
Nikolaus Kriegeskorte
◽
Peter König
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Tim C. Kietzmann
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Neural Networks
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Deep Neural Networks
◽
Data Augmentation
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Representation of adversarial images in deep neural networks and the human brain
10.32470/ccn.2018.1066-0
◽
2018
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Author(s):
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Xiaohan Duan
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Ruyuan Zhang
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Li Tong
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Neural Networks
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Study on Intelligent Security Camera Systems for the Automated Detection of Nighttime Snatching Incidents using Deep Neural Networks
IEEJ Transactions on Industry Applications
◽
10.1541/ieejias.136.727
◽
2016
◽
Vol 136
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◽
pp. 727-734
◽
Cited By ~ 2
Author(s):
Itaru Nagayama
◽
Akira Miyahara
◽
Koichi Shimabukuro
Keyword(s):
Neural Networks
◽
Deep Neural Networks
◽
Automated Detection
◽
Camera Systems
◽
Intelligent Security
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Memory Requirement Reduction of Deep Neural Networks for Field Programmable Gate Arrays Using Low-Bit Quantization of Parameters
2020 28th European Signal Processing Conference (EUSIPCO)
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10.23919/eusipco47968.2020.9287739
◽
2021
◽
Author(s):
Niccolo Nicodemo
◽
Gaurav Naithani
◽
Konstantinos Drossos
◽
Tuomas Virtanen
◽
Roberto Saletti
Keyword(s):
Neural Networks
◽
Deep Neural Networks
◽
Field Programmable Gate Arrays
◽
Memory Requirement
◽
Gate Arrays
◽
Field Programmable
◽
Programmable Gate Arrays
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The Use of Deep Neural Networks to Predict Post-liver Transplant Mortality
10.26226/morressier.58eb975cd462b80290b4f9e3
◽
2017
◽
Author(s):
Brent Ershoff
Keyword(s):
Neural Networks
◽
Liver Transplant
◽
Deep Neural Networks
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Financial Market Prediction and Improving the Performance Based on Large-scale Exogenous Variables and Deep Neural Networks
Korean Institute of Smart Media
◽
10.30693/smj.2020.9.4.26
◽
2020
◽
Vol 9
(4)
◽
pp. 26-35
Author(s):
Sung Gil Cheon
◽
Ju Hong Lee
◽
Bum Ghi Choi
◽
Jae Won Song
Keyword(s):
Neural Networks
◽
Financial Market
◽
Large Scale
◽
Deep Neural Networks
◽
Exogenous Variables
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