Rapid classification of copper concentrate by portable laser-induced breakdown spectroscopy combined with transfer learning and deep convolutional neural network

Haochen Li; Tianyuan Liu; Yuchao Fu; Wanxiang Li; Meng Zhang; Xi Yang; Di Song; Jiaqi Wang; You Wang; Meizhen Huang

doi:10.3788/COL202321.043001

Chinese Optics Letters, Volume. 21, Issue 4, 043001(2023)

Rapid classification of copper concentrate by portable laser-induced breakdown spectroscopy combined with transfer learning and deep convolutional neural network

Haochen Li¹, Tianyuan Liu^2、*, Yuchao Fu¹, Wanxiang Li¹, Meng Zhang³, Xi Yang³, Di Song³, Jiaqi Wang³, You Wang³, and Meizhen Huang¹

Author Affiliations

¹Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

²Department of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

³Southwest Institute of Technical Physics, Chengdu 610041, China

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Cited By

[1] Yue Pan, Motong Hu, Kailin Zhang, Xiping Xu.

[2] Yu Mao, Zixin Wang, Chang Xu, Yan Wang, Ningning Dong, Jun Wang.

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Haochen Li, Tianyuan Liu, Yuchao Fu, Wanxiang Li, Meng Zhang, Xi Yang, Di Song, Jiaqi Wang, You Wang, Meizhen Huang. Rapid classification of copper concentrate by portable laser-induced breakdown spectroscopy combined with transfer learning and deep convolutional neural network[J]. Chinese Optics Letters, 2023, 21(4): 043001

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Paper Information

Category: Spectroscopy

Received: Oct. 13, 2022

Accepted: Nov. 28, 2022

Published Online: Apr. 10, 2023

The Author Email: Tianyuan Liu (tianyuanl@sjtu.edu.cn)

DOI:10.3788/COL202321.043001

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology