Evolutionary Multi-Objective One-Shot Filter Pruning for Designing Lightweight Convolutional Neural Network

Deep neural networks have achieved significant development and wide applications for their amazing performance. However, their complex structure, high computation and storage resource limit their applications in mobile or embedding devices such as sensor platforms. Neural network pruning is an effic...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 21; H. 17; S. 5901
Hauptverfasser:	Wu, Tao, Shi, Jiao, Zhou, Deyun, Zheng, Xiaolong, Li, Na
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 02.09.2021 MDPI
Schlagworte:	Accuracy Algorithms convolutional neural network Datasets evolutionary multi-objective algorithm filter pruning lightweight model Methods Natural language processing Neural networks Optimization
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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