CNN-Based Plant Disease Detection from Leaf Images

Crop diseases pose a significant threat to global food security, and accurately identifying these ‎diseases remains a challenging task. Various diseases—such as gray leaf spot, common rust, ‎northern leaf blight, and others—affect different parts of the plant, including leaves, stems, and ‎roots, ultimately leading to substantial yield losses. Given the wide range of disease types and ‎their visual similarities, manual classification by human experts is both time-consuming and ‎prone to high error rates. To address these challenges, there is a growing need for automated ‎systems capable of detecting and classifying plant leaf diseases with high accuracy. This ‎technical review paper presents a comprehensive overview of common plant diseases, their ‎classifications, and the techniques employed to manage them. Additionally, it explores existing ‎literature and recent advancements in deep learning-based approaches, particularly those using ‎publicly available benchmark datasets for automated plant leaf disease detection and ‎classification‎.