scholarly journals Random sketch learning for deep neural networks in edge computing

2021 ◽  
Vol 1 (3) ◽  
pp. 221-228 ◽  
Author(s):  
Bin Li ◽  
Peijun Chen ◽  
Hongfu Liu ◽  
Weisi Guo ◽  
Xianbin Cao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Edge Computing

scholarly journals Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 212177-212193
Author(s):  
Yoshitomo Matsubara ◽  
Davide Callegaro ◽  
Sabur Baidya ◽  
Marco Levorato ◽  
Sameer Singh
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Edge Computing ◽  
Resource Constrained ◽  
Computing Systems

scholarly journals The Case for Adaptive Deep Neural Networks in Edge Computing

2021 ◽  
Author(s):  
Francis McNamee ◽  
Schahram Dustdar ◽  
Peter Kilpatrick ◽  
Weisong Shi ◽  
Ivor Spence ◽  
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Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Edge Computing

scholarly journals Hybrid Deep Neural Networks for Friend Recommendations in Edge Computing Environment

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 10693-10706
Author(s):  
Jibing Gong ◽  
Yi Zhao ◽  
Shuai Chen ◽  
Hongfei Wang ◽  
Linfeng Du ◽  
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Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Edge Computing ◽  
Computing Environment ◽  
Friend Recommendations

Full Python Interface Control: Auto Generation And Adaptation of Deep Neural Networks For Edge Computing and IoT Applications FPGA-Based Acceleration

2021 ◽  
Author(s):  
Tarek Belabed ◽  
Alexandre Quenon ◽  
Vitor Ramos Gomes Da Silva ◽  
Carlos A. Valderrama Sakuyama ◽  
Chokri Souani
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Edge Computing ◽  
Iot Applications ◽  
Interface Control

scholarly journals Performance analysis of local exit for distributed deep neural networks over cloud and edge computing

ETRI Journal ◽  
2020 ◽  
Vol 42 (5) ◽  
pp. 658-668
Author(s):  
Changsik Lee ◽  
Seungwoo Hong ◽  
Sungback Hong ◽  
Taeyeon Kim
Keyword(s):  
Neural Networks ◽  
Performance Analysis ◽  
Deep Neural Networks ◽  
Edge Computing

scholarly journals User Driven FPGA-Based Design Automated Framework of Deep Neural Networks For Low-Power Low-Cost Edge Computing

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
TaRek Belabed ◽  
Maria Gracielly F. Coutinho ◽  
Marcelo A. C. Fernandes ◽  
Carlos Valderrama ◽  
Chokri Souani
Keyword(s):  
Neural Networks ◽  
Low Power ◽  
Deep Neural Networks ◽  
Low Cost ◽  
Edge Computing
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