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BLASTING, Volume. 41, Issue 3, 240(2024)

Intelligent Classification of Blastability for Open-pit Uranium Mine based on Deep Learning

LIU Yu-long1... FU Hai-ying2, HUANG Lei1, LING Yang2, LIAN Meng2, LI Feng2, XIE Feng3 and DING De-xin2,* |Show fewer author(s)
Author Affiliations
  • 1China General Nuclear Power Group (CGN) Uranium Resources Co., Ltd., Beijing 100029, China
  • 2Key Discipline Laboratory for National Defense for Biotechnology in Uranium Mining and Hydrometallurgy, University of South China, Hengyang 421001, China
  • 3North Blasting Technology Co., Ltd., Beijing 100097, China
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    LIU Yu-long, FU Hai-ying, HUANG Lei, LING Yang, LIAN Meng, LI Feng, XIE Feng, DING De-xin. Intelligent Classification of Blastability for Open-pit Uranium Mine based on Deep Learning[J]. BLASTING, 2024, 41(3): 240

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    Paper Information

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    Received: Jun. 20, 2023

    Accepted: Dec. 20, 2024

    Published Online: Dec. 20, 2024

    The Author Email: De-xin DING (dingdxzzz@163.com)

    DOI:10.3963/j.issn.1001-487x.2024.03.028

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology