Tomato Leaf Disease Detection Using CNN Models

Tomato plants are vulnerable to different types of diseases, which can lead to significant reductions in yield and quality. Accurate and early detection is therefore crucial to mitigate these losses. This research proposes the use of deep learning approach for detecting tomato leaf diseases by utilizing Convolutional Neural Networks (CNNs). The study employs a custom CNN model and transfer learning techniques, and also utilize a large dataset of tomato leaf images. The proposed approaches showed promising result with high accuracy in distinguishing between healthy and diseased leaves.