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Rethinking Motivation of Deep Neural Architectures
Luo, Weilin1; Lu, Jinhu1,2,3,4,5,6; Li, Xuerong7; Chen, Lei1,3,8; Liu, Kexin1,9
2020
Source PublicationIEEE CIRCUITS AND SYSTEMS MAGAZINE
ISSN1531-636X
Volume20Issue:4Pages:65-76
AbstractNowadays, deep neural architectures have acquired great achievements in many domains, such as image processing and natural language processing. In this paper, we hope to provide new perspectives for the future exploration of novel artificial neural architectures via reviewing the proposal and development of existing architectures. We first roughly divide the influence domain of intrinsic motivations on some common deep neural architectures into three categories: information processing, information transmission and learning strategy. Furthermore, to illustrate how deep neural architectures are motivated and developed, motivation and architecture details of three deep neural networks, namely convolutional neural network (CNN), recurrent neural network (RNN) and generative adversarial network (GAN), are introduced respectively. Moreover, the evolution of these neural architectures are also elaborated in this paper. At last, this review is concluded and several promising research topics about deep neural architectures in the future are discussed.
DOI10.1109/MCAS.2020.3027222
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000612854700005
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/58089
Collection系统科学研究所
Corresponding AuthorLu, Jinhu
Affiliation1.Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China
2.Chinese Acad Sci, AMSS, Beijing, Peoples R China
3.RMIT Univ, Melbourne, Vic, Australia
4.Princeton Univ, Princeton, NJ 08544 USA
5.Natl Key Res & Dev Program China, Beijing, Peoples R China
6.Innovat Res Grp NNSF China, Beijing, Peoples R China
7.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
8.Okayama Prefectural Univ, Soja, Japan
9.Peking Univ, Beijing, Peoples R China
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GB/T 7714
Luo, Weilin,Lu, Jinhu,Li, Xuerong,et al. Rethinking Motivation of Deep Neural Architectures[J]. IEEE CIRCUITS AND SYSTEMS MAGAZINE,2020,20(4):65-76.
APA Luo, Weilin,Lu, Jinhu,Li, Xuerong,Chen, Lei,&Liu, Kexin.(2020).Rethinking Motivation of Deep Neural Architectures.IEEE CIRCUITS AND SYSTEMS MAGAZINE,20(4),65-76.
MLA Luo, Weilin,et al."Rethinking Motivation of Deep Neural Architectures".IEEE CIRCUITS AND SYSTEMS MAGAZINE 20.4(2020):65-76.
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