Abstract:
This article provides an overview of existing convolutional neural network architectures
and their application in the classification task for detecting diseases of fruits and plants. Diseases of
plants and fruits are a serious problem in agriculture and horticulture, and their early detection can
help in taking timely measures to prevent the spread and minimize damage. The results of the study
can be useful for the development of automated systems for detecting diseases of fruits and plants,
which helps to increase yields.
Citation:
M. A. Shereuzheva, M. A. Shereuzhev, Z. M. Albekova, “The use of convolutional neural networks
for automatic diseases detection tasks”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 5, 41–51
\Bibitem{SheSheAlb23}
\by M.~A.~Shereuzheva, M.~A.~Shereuzhev, Z.~M.~Albekova
\paper The use of convolutional neural networks
for automatic diseases detection tasks
\jour News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences
\yr 2023
\issue 5
\pages 41--51
\mathnet{http://mi.mathnet.ru/izkab713}
\crossref{https://doi.org/10.35330/1991-6639-2023-5-115-41-51}
\elib{https://elibrary.ru/item.asp?id=https://www.elibrary.ru/item.asp?id=54751394}
\edn{https://elibrary.ru/GOUNQN}