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Machine Learning-Enhanced Flexible Mechanical Sensing

Yuejiao Wang Mukhtar Lawan Adam Yunlong Zhao Weihao Zheng Libo Gao Zongyou Yin Haitao Zhao

纳微快报（英文）2023，Vol.15Issue(4)：190-222,33.

Machine Learning-Enhanced Flexible Mechanical Sensing

Yuejiao Wang ¹Mukhtar Lawan Adam ²Yunlong Zhao ³Weihao Zheng ⁴Libo Gao ³Zongyou Yin ⁵Haitao Zhao²

作者信息

1. Applied Mechanics Laboratory,Department of Engineering Mechanics,Tsinghua University,Beijing 100084,People's Republic of China
2. Materials Interfaces Center,Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,People's Republic of China
3. Department of Mechanical and Electrical Engineering,Xiamen University,Xiamen 361102,People's Republic of China
4. School of Mechano-Electronic Engineering,Xidian University,Xi'an 710071,People's Republic of China
5. Research School of Chemistry,Australian National University,Canberra,ACT 2601,Australia
折叠

摘要

关键词

Flexible mechanical sensors/Machine learning/Artificial intelligence/Data processing

Key words

Flexible mechanical sensors/Machine learning/Artificial intelligence/Data processing

引用本文复制引用

Yuejiao Wang,Mukhtar Lawan Adam,Yunlong Zhao,Weihao Zheng,Libo Gao,Zongyou Yin,Haitao Zhao..Machine Learning-Enhanced Flexible Mechanical Sensing[J].纳微快报（英文）,2023,15(4):190-222,33.

基金项目

These authors would like to acknowledge the financial support from National Natural Science Foundation of China(Nos.62274140,61904141,52173234),the State Key Labo-ratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(Grant No.MCMS-E-0422G03),the Shenzhen-Hong Kong-Macau Technology Research Program(Type C,202011033000145,SGDX2020110309300301).Open access funding provided by Shanghai Jiao Tong University. （Nos.62274140,61904141,52173234）

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ISSN：2311-6706

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