Tomato Leaf Disease Detection Using Deep Learning and Flask.
Year: 2025
Type: article
Abstract: Tomato plants are vulnerable to various leaf diseases that reduce crop yield and quality. This project uses deep learning, specifically a Convolutional Neural Network (CNN), to detect and classify tomato leaf diseases accurately. A dataset containing images of healthy and diseased leaves is used for training and validation. The model is deployed via a Flask web application, enabling users to upload leaf images and receive instant diagnosis. This system provides an accessible and cost-effective tool for early disease detection. It aims to support farmers and improve tomato crop management efficiently.
Authors: Nagaveni B Biradar, Farida P, Yashoda, Sneha R, Tejeshwari T
Institution: Visvesvaraya Technological University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6949262332
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