Spectral domain convolutional neural network optimized for computational workload and memory access cost
Conventional convolutional neural networks (CNNs), which are realized in the spatial domain, present a high computationalworkload and memory access cost (CMC). Spectral domain CNNs (SpCNNs) offer a computationally efficient approach for performing CNN training and inference. State-of-the-art SpCNNs...
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| Format: | Thèse |
| Langue: | anglais |
| Publié: |
2023
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| Accès en ligne: | http://eprints.utm.my/102817/1/ShahriyarMasudRizviPSKE2023.pdf.pdf |