Deep Learning Based Tomato Plant Disease Detection: A Review on Challenges and Future Directions

Many diseases that greatly affect crop output and quality are quite likely to strike tomato plants. Conventional disease detection techniques rely on time-consuming manual inspection prone to mistakes. By means of automatic, accurate, and real-time identification, recent developments in deep learning have transformed plant disease detection. This review investigates the use of deep learning methods for tomato plant disease diagnosis using convolutional neural networks (CNNs), You Only Look Once (YOLO), and other state-of- the-art models. We also go over publicly accessible datasets, difficulties, and next directions for study in this field.