Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/29153
Title: Methodology and Technology of Using Neural Networks in Agriculture
Authors: Mikhailov, G. G.
Михайлов, Г. Г.
Orobinskaya, V. N.
Оробинская, В. Н.
Kostoglotov, A. A.
Костоглотов, А. А.
Lavrova, T. N.
Лаврова, Т. Н.
Keywords: Agriculture;Unmanned aerial vehicles;Agro-industrial complex (AIC);Artificial intelligence;Artificial neural networks;Competencies;Computer vision;Forecasting;Optimization;Pattern;Training of highly qualified personnel
Issue Date: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Mikhailov, G.G., Orobinskaya, V.N., Pachina, N.N., Kostoglotov, A.A., Lavrova, T.N., Blinnikov, V.A. Methodology and Technology of Using Neural Networks in Agriculture // Proceedings - 2024 4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024. - 2024. - pp. 198-202. - DOI: 10.1109/TELE62556.2024.10605615
Series/Report no.: Proceedings - 2024 4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024
Abstract: The use of modern computer technologies in both industrial and service sectors is an evolutionary development associated with reducing infrastructure costs for all industrial enterprises and improving working conditions. In this regard, training in the field of information technology is becoming increasingly popular. The organization of innovative learning spaces, research into the methodology and technology of using neural networks in agriculture is relevant and in demand. The training of highly qualified personnel is aimed at mastering a group of competencies related to automation in the agricultural sector. Thus, computer vision has begun to be frequently used in the agricultural sector, as it helps with the automation of monitoring crops and animals. It can perform many functions in semi- or automatic mode, such as: monitoring and recognizing crops, identifying plant pathologies, studying animal patterns and making predictions based on the data obtained. Important competencies are related to the ability to use unmanned aerial vehicles (UAVs) in areas related to agricultural production, livestock farming, which involves keeping large and small livestock, crop production, aerial photography of arable land, and optimization of the consumption of resources necessary to maintain the stable operation of the agro-industrial complex (herbicides, pesticides, fertilizers and chemicals), which are also covered in the study.
URI: https://dspace.ncfu.ru/handle/123456789/29153
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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