An analysis of plant diseases identification based on deep learning methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ACFJJAFRD" target="_blank" >RIV/00216208:11320/23:CFJJAFRD - isvavai.cz</a>
Result on the web
<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412967/" target="_blank" >https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412967/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5423/ppj.oa.02.2023.0034" target="_blank" >10.5423/ppj.oa.02.2023.0034</a>
Alternative languages
Result language
angličtina
Original language name
An analysis of plant diseases identification based on deep learning methods
Original language description
"Recent developments in deep learning, especially convolutional neural network (CNN), have shown impressive performance in plant disease classification."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"The Plant Pathology Journal"
ISSN
2093-9280
e-ISSN
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Volume of the periodical
39
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
319
Pages from-to
1-319
UT code for WoS article
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EID of the result in the Scopus database
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