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 |
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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 |
页 | 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 | 是 |
活动 | 39th Chinese Control Conference, CCC 2020 - Shenyang, 中国 期限: 27 7月 2020 → 29 7月 2020 |
出版系列
姓名 | Chinese Control Conference, CCC |
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卷 | 2020-July |
ISSN(印刷版) | 1934-1768 |
ISSN(电子版) | 2161-2927 |
会议
会议 | 39th Chinese Control Conference, CCC 2020 |
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国家/地区 | 中国 |
市 | Shenyang |
时期 | 27/07/20 → 29/07/20 |
指纹
探究 'Convolutional Neural Network Pruning: A Survey' 的科研主题。它们共同构成独一无二的指纹。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