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, Issue 5,Pages <nobr>41

System analysis, management and information processing

The use of convolutional neural networks for automatic diseases detection tasks

M. A. Shereuzheva^ab, M. A. Shereuzhev^c, Z. M. Albekova^d

^a Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 360000, Russia, Nalchik, 37-a I. Armand street
^b Moscow State Technological University «STANKIN», 127055, Russia, Moscow, 1 Vadkovsky lane
^c Moscow State Technical University named after N. E. Bauman, 105005, Russia, Moscow, build. 5 corps 1 Baumanskaya street
^d Institute of Digital Development, North Caucasian Federal University, 350029, Russia, Stavropol, 2 Kulakov avenue

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.

Keywords: neural networks, machine learning, convolutional network architecture, computer vision, image classification.

UDC: 004.89

MSC: 68T99

Received: 25.09.2023
Revised: 06.10.2023
Accepted: 09.10.2023

DOI: 10.35330/1991-6639-2023-5-115-41-51