{"id":9736,"date":"2026-04-02T13:05:27","date_gmt":"2026-04-02T12:05:27","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=9736"},"modified":"2026-04-06T14:14:49","modified_gmt":"2026-04-06T13:14:49","slug":"25-5-4-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-5-4-en\/","title":{"rendered":"25.5.4 En"},"content":{"rendered":"\n

The use of convolutional neural networks for automatic diseases detection tasks<\/strong><\/h1>\n\n\n\n

M.A. Shereuzheva, M.A. Shereuzhev, Z.M. Albekova<\/strong><\/p>\n\n\n\n

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Upload the full text<\/strong><\/strong><\/p>\n\n\n\n

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Abstract<\/strong>:<\/strong> <\/em>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.<\/p>\n\n\n\n

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Keywords<\/strong>:<\/em><\/strong> neural networks, machine learning, convolutional network architecture, computer vision, image classification<\/p>\n\n\n\n

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For citation<\/strong>.<\/strong> Shereuzheva M.A., Shereuzhev M.A., Albekova Z.M. The use of convolutional neural networks for automatic diseases detection tasks. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 5(115). Pp. 41\u201351. DOI: 10.35330\/1991-6639-2023-5-115-41-51<\/p>\n\n\n\n

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R<\/strong>eferences<\/summary>\n
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  2. Shereuzheva M.A., Shereuzhev M.A. Development of expert systems to improve the efficiency of growing plants in agriculture. News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. 2022. No. 5(109). Pp. 93\u2013104. DOI: 10.35330\/1991-6639-2022-5-109-93-104. (In Russian)<\/li>\n\n\n\n
  3. Nagoev Z.V., Shuganov V.M., Bzhikhatlov K.Ch. et al. Prospects for increasing the productivity and efficiency of agricultural production with the use of an intelligent integrated environment. News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. 2021. No. 6(104). Pp. 155\u2013165. DOI: 10.35330\/1991-6639-2021-6-104-155-165. (In Russian)<\/li>\n\n\n\n
  4. Krizhevsky A., Sutskever I., Hinton G.E. ImageNet classification with deep convolutional neural networks. Communications of the ACM<\/em>. 2012. 60(6). Pp. 84\u201390. <\/li>\n\n\n\n
  5. Pushkarev A., Yakubailik O. A web application for visualization, analysis, and processing of agricultural monitoring spatial-temporal data. CEUR Workshop Proceedings<\/em>. 2021. Vol. 3006. Pp. 231\u2013237. URL: http:\/\/ceur-ws.org\/Vol-006\/27_short_paper.pdf<\/li>\n\n\n\n
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  11. Szegedy C. et al. Inception-v4, inception-resnet and the impact of residual connections on learning. Thirty-first AAAI conference on artificial intelligence<\/em>. 2017.<\/li>\n\n\n\n
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    Information about the authors<\/strong><\/summary>\n
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    Shereuzheva Milana Arturovna<\/strong>, master, Department \u201cInformation technologies and computing systems\u201d, Moscow Technical University \u201cSTANKIN\u201d;
    127055, Russia, Moscow, 1 Vadkovsky lane;
    trainee researcher of the Laboratory \u201cIntellectual Habitats\u201d of the Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 37-a I. Armand street;
    milana.shereuzheva@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-6668-4703
    Shereuzhev Madin Arturovich<\/strong>, senior lecturer, Department \u201cRobotic systems and mechatronics\u201d, Moscow State Technical University named after N.E. Bauman;
    105005, Russia, Moscow, build. 5 corps 1 Baumanskaya street;
    shereuzhev@bmstu.ru, ORCID: https:\/\/orcid.org\/0000-0003-2352-992\u0425
    Albekova Zamira Mukhamedalievna<\/strong>, Candidate of Pedagogical Sciences, Associate Professor, Department of Information Systems and Technologies, Institute of Digital Development, North Caucasus Federal University;
    350029, Russia, Stavropol, 2 Kulakov avenue;
    zalbekova@ncfu.ru, ORCID: https:\/\/orcid.org\/0000-0002-7214-8114<\/p>\n\n\n\n

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    The use of convolutional neural networks for automatic diseases detection tasks M.A. Shereuzheva, M.A. Shereuzhev, Z.M. Albekova Upload the full text 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 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"wp-custom-template-home","meta":{"footnotes":""},"class_list":["post-9736","page","type-page","status-publish","hentry"],"yoast_head":"\n25.5.4 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-5-4-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"25.5.4 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"The use of convolutional neural networks for automatic diseases detection tasks M.A. Shereuzheva, M.A. Shereuzhev, Z.M. 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