Tomato Leaf Disease Detection and Classification using Convolutional Neural Networks

Automatic classification process in images has been used in many fields, especially agriculture and medical fields in recent years. Especially in our country, image processing studies are needed to improve agriculture and increase productivity in agriculture. In this study, the major tomato leaf diseases that significantly affect tomato efficiency were examined and the convolutional neural networks deep learning method was applied for the automatic classification of these diseases. It is thought that the model applied in this study can also be applied on other agricultural crops, so that the contribution of image processing to agriculture will increase gradually. This study can also be used for a robot that can complete the detection and classification of plant diseases automatically by performing a tour of inspection in a particular region.