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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| 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 |