CNN-Based Plant Disease Diagnosis: A Step Towards Sustainable Farming

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.

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Publication Details

Published
2025-04-15
DOI
https://doi.org/10.38124/ijisrt/25mar1972
Primary Topic
Smart Agriculture and AI
Type
article
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CNN-Based Plant Disease Diagnosis: A Step Towards Sustainable Farming

M. Sailaja, Amira Sharief, A. Malavika, Yarraboina Chaitanya Vamsi et al.
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Smart Agriculture and AI
article

CNN-Based Plant Disease Diagnosis: A Step Towards Sustainable Farming

M. Sailaja, Amira Sharief, A. Malavika, Yarraboina Chaitanya Vamsi, K Jahnavi, Mekala Vujwal
article en

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.

Openalex Percentile: Top 95%
Smart Agriculture and AI
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CNN-Based Plant Disease Diagnosis: A Step Towards Sustainable Farming — M. Sailaja, Amira Sharief, et al. · (2025) | TGRS Research Map | TGRS