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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Main Authors: | , , , , |
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Format: | Article |
Published: |
Springer
2023
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Subjects: | |
Online Access: | http://eprints.utm.my/105057/ http://dx.doi.org/10.1007/s10489-022-03756-1 |
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Institution: | Universiti Teknologi Malaysia |