Efficient Detection of Longitudinal Bacteria Fission Using Transfer Learning in Deep Neural Networks

Efficient Detection of Longitudinal Bacteria Fission Using Transfer Learning in Deep Neural Networks

A very common way to classify bacteria is through microscopic images. Microscopic cell counting is a widely used technique to measure microbial growth. To date, fully automated methodologies are available for accurate and fast measurements; yet for bacteria dividing longitudinally, as in the case of...

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Bibliographic Details
Main Authors: Carlos Garcia-Perez, Keiichi Ito, Javier Geijo, Roman Feldbauer, Nico Schreiber, Wolfgang zu Castell
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Microbiology
Subjects:
bacteria division
longitudinal bacterial fission
bacteria classification
deep learning
transfer learning
image processing
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2021.645972/full

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https://www.frontiersin.org/articles/10.3389/fmicb.2021.645972/full

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