Authors : N Bhavana; P Likithasree

Volume/Issue : Volume 10 - 2025, Issue 4 - April

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Google Scholar : https://tinyurl.com/yc6xdvrp

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DOI : https://doi.org/10.38124/ijisrt/25apr2394

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Abstract : Plant diseases pose a major danger to agricultural productivity and global food security. In order to automatically detect plant diseases, this study presents a deep learning-based technique for categorising leaf photos. The system uses Convolutional Neural Networks (CNNs) constructed in PyTorch to identify 39 different forms of plant diseases using the PlantVillage dataset. A pre-trained model is integrated into an intuitive Flask web application, allowing users—farmers in particular—to submit leaf photographs and receive prompt, accurate diagnoses. The model learns intricate visual patterns associated with many plant diseases, offering an efficient, scalable, and cost-effective method for early disease diagnosis and control in agriculture.

Keywords : Plant Health Monitoring, CNN Classification, Leaf Disease Detection, Smart Farming, Precision Agriculture.

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