Resilient training of neural network classifiers with approximate computing techniques for hardware‐optimised implementations
Author:
Affiliation:
1. Graduate Program in Electrical Engineering – UFMG – Av. Antonio Carlos 662731270‐901Belo HorizonteMGBrazil
2. Cyber‐Physical SystemsDFKI GmbHBibliothekstraße 528359BremenGermany
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Hardware and Architecture,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cdt.2019.0036
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