Convolutional Neural Network Pruning: A Survey

Sheng Xu, Anran Huang, Lei Chen*, Baochang Zhang

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

43 引用 (Scopus)
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摘要

Deep convolutional neural networks have enabled remarkable progress over the last years on a variety of visual tasks, such as image recognition, speech recognition, and machine translation. These tasks contribute many to machine intelligence. However, developments of deep convolutional neural networks to a machine terminal remains challenging due to massive number of parameters and float operations that a typical model contains. Therefore, there is growing interest in convolutional neural network pruning. Existing work in this field of research can be categorized according to three dimensions: pruning method, training strategy, estimation criterion.

源语言英语
主期刊名Proceedings of the 39th Chinese Control Conference, CCC 2020
编辑Jun Fu, Jian Sun
出版商IEEE Computer Society
7458-7463
页数6
ISBN(电子版)9789881563903
DOI
出版状态已出版 - 7月 2020
已对外发布
活动39th Chinese Control Conference, CCC 2020 - Shenyang, 中国
期限: 27 7月 202029 7月 2020

出版系列

姓名Chinese Control Conference, CCC
2020-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议39th Chinese Control Conference, CCC 2020
国家/地区中国
Shenyang
时期27/07/2029/07/20

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引用此

Xu, S., Huang, A., Chen, L., & Zhang, B. (2020). Convolutional Neural Network Pruning: A Survey. 在 J. Fu, & J. Sun (编辑), Proceedings of the 39th Chinese Control Conference, CCC 2020 (页码 7458-7463). 文章 9189610 (Chinese Control Conference, CCC; 卷 2020-July). IEEE Computer Society. https://doi.org/10.23919/CCC50068.2020.9189610