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Deep Learning for Imaging and Detection of Microorganisms.
Zhang, Yang; Jiang, Hao; Ye, Taoyu; Juhas, Mario.
Afiliação
  • Zhang Y; College of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, 518055, China. Electronic address: zhangyang07@hit.edu.cn.
  • Jiang H; College of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, 518055, China.
  • Ye T; College of Science, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, 518055, China.
  • Juhas M; Medical and Molecular Microbiology Unit, Department of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland.
Trends Microbiol ; 29(7): 569-572, 2021 07.
Article em En | MEDLINE | ID: mdl-33531192
ABSTRACT
Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenges faced by human-operated microscopy, deep-learning-based methods have been proposed for microscopic image analysis of a wide range of microorganisms, including viruses, bacteria, fungi, and parasites. We believe that deep-learning technology-based systems will be on the front line of monitoring and investigation of microorganisms.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Doenças Transmissíveis / Aprendizado Profundo / Microscopia Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Trends Microbiol Assunto da revista: MICROBIOLOGIA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Doenças Transmissíveis / Aprendizado Profundo / Microscopia Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Trends Microbiol Assunto da revista: MICROBIOLOGIA Ano de publicação: 2021 Tipo de documento: Article