Artificial intelligence is used to identify tomato diseases through leaf analysis

This paper explores using artificial intelligence (AI) in applications to detect tomato leaf diseases. A key issue is how automated systems and artificial intelligence can be used to diagnose and predict disease control, damage, and temporary control of tomato diseases. The paper is based on the study of the benefits of implementing classical and modern artificial intelligence models, their problems, and successful technological solutions in detecting tomato diseases. The article describes in detail how effective distributed artificial intelligence algorithms are in detecting tomato diseases, their application, and their independence in analyzing and accounting for the results. As a result, it is important to use artificial intelligence to detect tomato leaf diseases quickly, and this discovery offers effective methods for faster treatment. Tomato export is considered important for the economy of Uzbekistan, one of the developing agricultural countries today [1,2]. However, even in this area, there are cases of crop loss, so we created and analyzed a project that detects tomato leaf diseases based on deep learning with transfer learning architectures.

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