4.7 Editorial Material

Deep Learning for Imaging and Detection of Microorganisms

Journal

TRENDS IN MICROBIOLOGY
Volume 29, Issue 7, Pages 569-572

Publisher

CELL PRESS
DOI: 10.1016/j.tim.2021.01.006

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Funding

  1. Natural Science Foundation of Shenzhen City [JCYJ20180306172131515]

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Despite the significant interest in deep learning in microbiology, its full potential is yet to be realized. Deep-learning-based systems are believed to play a crucial role in monitoring and investigating microorganisms in the future.
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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