TY - JOUR AU - Kompalli, Prasanna Lakshmi AU - Mekala, Keerthana Reddy AU - Modala, Venkata Sai Rupa Sree AU - Devalla, Varsha AU - Kompalli, Avinash Bhargav PY - 2022/06/14 Y2 - 2024/03/28 TI - Leaf Disease Detection and Remedy Recommendation Using CNN Algorithm JF - International Journal of Online and Biomedical Engineering (iJOE) JA - Int. J. Onl. Eng. VL - 18 IS - 07 SE - Papers DO - 10.3991/ijoe.v18i07.30383 UR - https://online-journals.org/index.php/i-joe/article/view/30383 SP - pp. 85-100 AB - <p>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</p> ER -