Plant Disease Detection Using Convolutional Neural Networks (CNNs)

Author(s)	Kuldeep Dilliwar, Subham Mandal, Nagesh Sahu, Manish Kumar Shriwas, Rajeshri Lanjewar
Country	India
Abstract	Plant disease detection is crucial for ensuring agri-cultural productivity and food security. However, accurately identifying diseases across various crops remains a challenge, particularly in resource-constrained regions. This study addresses this issue by developing a single convolutional neural network (CNN) model capable of identifying diseases across multiple crop types. Using a comprehensive dataset containing labelled images of healthy and diseased leaves from various crops: including apples, potatoes, and bell peppers, the model was trained to recognize both the crop type and the specific disease.
Keywords	Plant Disease Detection (PDD), Convolutional Neural Network (CNN)
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-05-02
Cite This	Plant Disease Detection Using Convolutional Neural Networks (CNNs) - Kuldeep Dilliwar, Subham Mandal, Nagesh Sahu, Manish Kumar Shriwas, Rajeshri Lanjewar - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.4367
DOI	https://doi.org/10.71097/IJSAT.v16.i2.4367
Short DOI	https://doi.org/g9hbsm

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