Мақола

Diagnostics of plant diseases based on symptoms from leaf images

Dilnoz MuhamediyevaTashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, UzbekistanNozir TukhtamuradovTashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, UzbekistanBoymirzo SamijonovSejong University, South Korea, Seoul, KoreaJurabek UsarovTashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, UzbekistanBobur JumayevTashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, Uzbekistan

BIO Web of Conferencesjournal2025en

ABI

Аннотация

The paper develops algorithms for diagnosing plant diseases based on symptoms from leaf images. Various features, such as changes in color, shape, and texture of leaves, associated with diseases are analyzed. It investigates how symptoms affect the accuracy of disease recognition using machine learning. It is revealed that the use of visual symptoms and other symptoms significantly improves diagnostic results. Not only that but it is determined that the combination of deep learning and classical image processing methods allows for high accuracy in disease detection. Furthermore, it is established that the developed algorithms can identify plant diseases based on symptoms detected in leaf images. The results of testing the algorithms on real data show their applicability in the real world.

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Мавзулар

Smart Agriculture and AI Leaf Properties and Growth Measurement Greenhouse Technology and Climate Control

Идентификаторлар

DOI: 10.1051/bioconf/202516001004

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