Using Algorithmic Transformations and Sensitivity Analysis to Unleash Approximations in CNNs at the Edge

Previous studies have demonstrated that, up to a certain degree, Convolutional Neural Networks (CNNs) can tolerate arithmetic approximations. Nonetheless, perturbations must be applied judiciously, to constrain their impact on accuracy. This is a challenging task, since the implementation of inexact...

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Detalles Bibliográficos
Autores principales: Ponzina, Flavio, Ansaloni, Giovanni, Peón-Quirós, Miguel, Atienza, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320279/
https://www.ncbi.nlm.nih.gov/pubmed/35888960
http://dx.doi.org/10.3390/mi13071143

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320279/
https://www.ncbi.nlm.nih.gov/pubmed/35888960
http://dx.doi.org/10.3390/mi13071143

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