Plant leaf disease classification using deep neural network Online publication date: Wed, 07-Sep-2022
by N. Kasthuri; T. Meera Devi; Arivazhagan T. Shangar; R. Yashwin; J.S. Shabhareesh
International Journal of Computational Vision and Robotics (IJCVR), Vol. 12, No. 5, 2022
Abstract: Agriculture is the backbone of Indian economy. Most of the people living in rural areas depend on agriculture for their livelihood. Nevertheless, the farmers are facing a lot of difficulties in crop production due to climatic change. In addition, diseases in plants affect the production of crops drastically. Presently, the farmers identify the plant diseases by visual inspection which, in turn, requires an expert's help and it is a time consuming task. Hence, in this paper, deep learning networks are used to identify different types of diseases in the leaves of different plants. The model is trained with 45,562 images and validated with 8,049 images belonging to 17 categories of diseases. It is fine-tuned with the hyperparameters such as learning rate, epochs, batch size and input image size and then tested with 9,469 images which yield a total classification accuracy of 96.8%.
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