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

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

Deep Learning techniques have been successfully applied to solve many Artificial Intelligence (AI) applications problems. However, owing to topologies with many hidden layers, Deep Neural Networks (DNNs) have high computational complexity, which makes their deployment difficult in contexts highly co...

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Bibliographic Details
Main Authors: Tarek Belabed, Maria Gracielly F. Coutinho, Marcelo A. C. Fernandes, Carlos Valderrama Sakuyama, Chokri Souani
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning
electronic design automation
edge computing
FPGA
low power systems
Online Access:https://ieeexplore.ieee.org/document/9458248/

Internet

https://ieeexplore.ieee.org/document/9458248/

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