A forward error compensation approach for fault resilient deep neural network accelerator design

A forward error compensation approach for fault resilient deep neural network accelerator design

Deep learning accelerator is a key enabler of a variety of safety-critical applications such as self-driving car and video surveillance. However, recently reported hardware-oriented attack vectors, e.g., fault injection attacks, have extended the threats on deployed deep neural network (DNN) systems...

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書目詳細資料
Main Authors:	Liu, Wenye, Chang, Chip Hong
其他作者:	School of Electrical and Electronic Engineering
格式:	Conference or Workshop Item
語言:	English
出版:	2022
主題:	Engineering::Electrical and electronic engineering::Computer hardware, software and systems Hardware Security Fault Injection Attack Deep Neural Network Accelerator
在線閱讀:	https://hdl.handle.net/10356/155879
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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