Computation and memory optimized spectral domain convolutional neural network for throughput and energy-efficient inference

Conventional convolutional neural networks (CNNs) present a high computational workload and memory access cost (CMC). Spectral domain CNNs (SpCNNs) offer a computationally efficient approach to compute CNN training and inference. This paper investigates CMC of SpCNNs and its contributing components...

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Detalles Bibliográficos
Autores principales: Rizvi, Shahriyar Masud, Rahman, Ab Al-Hadi Ab, Sheikh, Usman Ullah, Fuad, Kazi Ahmed Asif, Shehzad, Hafiz Muhammad Faisal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188280/
https://www.ncbi.nlm.nih.gov/pubmed/35730044
http://dx.doi.org/10.1007/s10489-022-03756-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188280/
https://www.ncbi.nlm.nih.gov/pubmed/35730044
http://dx.doi.org/10.1007/s10489-022-03756-1

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