A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): From Convolutional Neural Networks to Visual Transformers.
convolutional neural network
deep learning
environmental microorganism
image classification
small dataset
visual transformer
Journal
Frontiers in microbiology
ISSN: 1664-302X
Titre abrégé: Front Microbiol
Pays: Switzerland
ID NLM: 101548977
Informations de publication
Date de publication:
2022
2022
Historique:
received:
09
10
2021
accepted:
02
02
2022
entrez:
21
3
2022
pubmed:
22
3
2022
medline:
22
3
2022
Statut:
epublish
Résumé
In recent years, deep learning has made brilliant achievements in
Identifiants
pubmed: 35308350
doi: 10.3389/fmicb.2022.792166
pmc: PMC8924496
doi:
Types de publication
Journal Article
Langues
eng
Pagination
792166Informations de copyright
Copyright © 2022 Zhao, Li, Rahaman, Xu, Yang, Sun, Jiang and Grzegorzek.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Références
Anal Chim Acta. 2011 Oct 31;705(1-2):2-14
pubmed: 21962341
Sci Total Environ. 2017 Dec 31;609:1192-1199
pubmed: 28787793
IEEE Trans Image Process. 2018 Jan;27(1):293-303
pubmed: 28952941
Anal Bioanal Chem. 2008 Jun;391(4):1321-5
pubmed: 18327573
Med Image Comput Comput Assist Interv. 2015 Oct;9351:358-365
pubmed: 28090601
Front Microbiol. 2020 Sep 18;11:574966
pubmed: 33042087