A low functional redundancy-based network slimming method for accelerating deep neural networks

Deep neural networks (DNNs) have been widely criticized for their large parameters and computation demands, hindering deployment to edge and embedded devices. In order to reduce the floating point operations (FLOPs) running DNNs and accelerate the inference speed, we start from the model pruning, an...

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Bibliographic Details

Published in:	Alexandria Engineering Journal
Main Authors:	Zheng Fang, Bo Yin
Format:	Article
Language:	English
Published:	Elsevier 2025-04-01
Subjects:	Deep neural networks Network pruning Functional redundancy Contribution Ranking
Online Access:	http://www.sciencedirect.com/science/article/pii/S1110016824017162