Class-specific early exit design methodology for convolutional neural networks (2021)
Bonato, Vanderlei 
; Bouganis, Christos-Savvas
Source: Applied Soft Computing Journal. Unidade: ICMC
Subjects: HARDWARE, INFERÊNCIA, CONSUMO DE ENERGIA ELÉTRICA
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ABNT
BONATO, Vanderlei e BOUGANIS, Christos-Savvas. Class-specific early exit design methodology for convolutional neural networks. Applied Soft Computing Journal, v. 107, p. 1-12, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2021.107316. Acesso em: 03 jun. 2024.APA
Bonato, V., & Bouganis, C. -S. (2021). Class-specific early exit design methodology for convolutional neural networks. Applied Soft Computing Journal, 107, 1-12. doi:10.1016/j.asoc.2021.107316NLM
Bonato V, Bouganis C-S. Class-specific early exit design methodology for convolutional neural networks [Internet]. Applied Soft Computing Journal. 2021 ; 107 1-12.[citado 2024 jun. 03 ] Available from: https://doi.org/10.1016/j.asoc.2021.107316Vancouver
Bonato V, Bouganis C-S. Class-specific early exit design methodology for convolutional neural networks [Internet]. Applied Soft Computing Journal. 2021 ; 107 1-12.[citado 2024 jun. 03 ] Available from: https://doi.org/10.1016/j.asoc.2021.107316
