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An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm.
Zhang, Ji; Zhou, Yuanyuan; Vieira, Duarte Nuno; Cao, Yongjie; Deng, Kaifei; Cheng, Qi; Zhu, Yongzheng; Zhang, Jianhua; Qin, Zhiqiang; Ma, Kaijun; Chen, Yijiu; Huang, Ping.
Afiliação
  • Zhang J; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China.
  • Zhou Y; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China.
  • Vieira DN; Department of Forensic Medicine, Inner Mongolia Medical University, Huhhot, Inner Mongolia, People's Republic of China.
  • Cao Y; Department of Forensic Medicine, Ethics and Medical Law, Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
  • Deng K; Department of Forensic Medicine, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Cheng Q; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China.
  • Zhu Y; Department of Forensic Medicine, Guizhou Medical University, Guiyang, Guizhou, People's Republic of China.
  • Zhang J; School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi, People's Republic of China.
  • Qin Z; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China.
  • Ma K; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China.
  • Chen Y; Shanghai Key Laboratory of Crime Scene Evidence, Institute of Criminal Science and Technology, Shanghai Municipal Public Security Bureau, Shanghai, People's Republic of China. makaijun@sina.cn.
  • Huang P; Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, People's Republic of China. chenyj@ssfjd.cn.
Int J Legal Med ; 135(3): 817-827, 2021 May.
Article em En | MEDLINE | ID: mdl-33392655
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Factuais / Redes Neurais de Computação / Diatomáceas / Patologia Legal / Afogamento Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals País/Região como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Factuais / Redes Neurais de Computação / Diatomáceas / Patologia Legal / Afogamento Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals País/Região como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article