CNN-Based Plant Disease Diagnosis: A Step Towards Sustainable Farming
Year: 2025
Type: article
Abstract: The Crop Disease Detection System is an innovative solution that addresses challenges in modern agriculture. With the growing global population and increasing pressure on food production, effective crop disease management is crucial. This system harnesses machine learning and image recognition to help farmers, gardeners, and agricultural professionals accurately diagnose plant diseases. By uploading images of affected crops, users can rely on advanced deep learning algorithms to identify specific diseases and receive tailored recommendations for mitigation. Using a CNN-based approach trained on the PlantVillage dataset with transfer learning, the system automates disease detection, reducing dependence on manual inspection. Designed for real-time deployment, it can be integrated into agricultural advisory platforms, offering scalable support across diverse crop types and environmental conditions.
Authors: A H Sharief, Anumala Malavika, Matta Sailaja, Mekala Vujwal, Kantubuktha Jahnavi, Yarraboina Chaitanya Vamsi
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
OpenAlex ID: W4409461978