: 37-48
Received: March 08, 2024
Revised: April 01, 2024
Accepted: April 05, 2024
Lviv Polytechnic National University
Lviv Polytechnic National University

The article explores the use of convolutional neural networks (CNNs) in the diagnosis and identification of plant diseases and pests. Various methods of plant disease diagnosis, features of datasets, and challenges in this research direction are considered. The article discusses a five-step methodology for determining plant diseases, including data collection, preprocessing, segmentation, feature extraction, and classification. Different deep learning architectures enabling fast and efficient plant disease diagnosis are investigated. Innovative trends and issues in this field requiring further research and attention from the scientific community are highlighted

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