RESEARCH OF PLANT DISEASE DIAGNOSTIC METHODS USING DEEP LEARNING
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.