Leaf Disease Detection and Remedy Recommendation Using CNN Algorithm - Kompalli, Prasanna Lakshmi; Mekala, Keerthana Reddy; Modala, Venkata Sai Rupa Sree; Devalla, Varsha; Kompalli, Avinash Bhargav (International Journal of Online and Biomedical Engineering (iJOE), 2022)
In many countries, agriculture has an excess impact on life of human beings and economic status. As leaf plays an important role, it gives information about the quantity and quality of agriculture yield depending upon the condition in advance. In this paper, we proposed the system which focuses on the detection of disease in plant leaves using Deep Learning approach. The main two processes that we used in our system are GUL Application and Deep Learning. We used CNN for classification of diseases and Remedy Recommendation upon diseased leaf selected from the Plant Village Dataset. This dataset consists of both healthy and unhealthy leaves. Our results show that the CNN Model achieves 96% accuracy for 8 epochs using Tensor flow