An energy-efficient convolution unit for depthwise separable convolutional neural networks

High performance but computationally expensive Convolutional Neural Networks (CNNs) require both algorithmic and custom hardware improvement to reduce model size and to improve energy efficiency for edge computing applications. Recent CNN architectures employ depthwise separable convolution to reduc...

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Bibliographic Details
Main Authors: Chong, Yi Sheng, Goh, Wang Ling, Ong, Yew-Soon, Nambiar, Vishnu P., Do, Anh Tuan
Other Authors: Interdisciplinary Graduate School (IGS)
Format: Conference or Workshop Item
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10356/152096
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Institution: Nanyang Technological University
Language: English

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