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Deep Neural Network-Based Electron Microscopy Image Recognition for Source Distinguishing of Anthropogenic and Natural Magnetic Particles.
Liu, Lin; Chen, Tianyou; Zhang, Qinghua; Zhang, Weican; Yang, Hang; Hu, Xiaoguang; Xiao, Jin; Liu, Qian; Jiang, Guibin.
Afiliação
  • Liu L; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Chen T; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
  • Zhang Q; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Zhang W; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Yang H; College of Geography and Environmental Science, Henan University, Kaifeng 475004, China.
  • Hu X; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Xiao J; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
  • Liu Q; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Jiang G; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Environ Sci Technol ; 57(43): 16465-16476, 2023 10 31.
Article em En | MEDLINE | ID: mdl-37801812

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Fenômenos Magnéticos Idioma: En Revista: Environ Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Fenômenos Magnéticos Idioma: En Revista: Environ Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China