Early Detection of Plant Leaf Disease Using Deep Learning
DOI:
https://doi.org/10.32628/IJSRST2184939Keywords:
Plant Leaf Disease, Deep Learning, CNN Algorithm, Image processing, Neural Network, AgricultureAbstract
As crop diseases spread, farmers need to prevent and control their contamination to increase productivity and yield. In addition to affecting plants, plant diseases affect market access and agricultural production. As one of the most important vegetable plants in the world, leaf images can be used to classify diseases early. In addition to Yellow Curved, Late Blight, and Leaf Spot, Bacterial leaf Spot, there are other diseases of plants. The dataset is taken from the Internet. In this paper, we take leaf images with various leaf diseases and train it with the best model Convolutional Neural Network (CNN). We then use the weights from CNN to test new leaf images. By using convolutional neural networks (CNNs) and deep learning techniques, we have proposed a system that classifies plant leaf diseases. With the hybrid approach, the model will demonstrate its accuracy. To identify the best model, performance analysis is done with accuracy and finds solution to the problem.
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