Plant Disease Detection Using Deep Learning
Author
Dr. K. R. Martin, Sharmila S
Abstract
Plant diseases can reduce crop quality and productivity when they are not identified at an early stage. Traditional disease identification usually depends on visual inspection by farmers or agricultural experts, which can be time-consuming and may vary with experience. This paper proposes a Plant Disease Detection system using Deep Learning to automatically identify diseases from images of plant leaves. A leaf image is captured or uploaded, pre-processed, and passed to a deep-learning model trained on labelled plant images. The model extracts visual features such as colour, texture, shape, and lesion patterns and predicts the corresponding disease class. The predicted result can be displayed through a simple application interface, helping users obtain a quick preliminary indication of plant health. The approach can support early detection, reduce manual inspection effort, and provide a foundation for smart agriculture applications.
Keywords
Plant Disease Detection, Deep Learning, Convolutional Neural Network, Image Classification, Computer Vision, Leaf Image, Smart Agriculture.
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References
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