Development of low-overhead soft error mitigation technique for safety critical neural networks applications

Deep Neural Networks (DNNs) have been widely applied in healthcare applications. DNN-based healthcare applications are safety-critical systems that require highreliability implementation due to a high risk of human death or injury in case of malfunction. Several DNN accelerators are used to execute...

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Auteur principal: Khalid Adam, Ismail Hammad
Format: Thèse
Langue:anglais
Publié: 2021
Sujets:
Accès en ligne:http://umpir.ump.edu.my/id/eprint/34715/1/Development%20of%20low-overhead%20soft%20error%20mitigation%20technique%20for%20safety%20critical%20neural.ir.pdf