Implementation of Peanut Leaf Disease Detection System Using Faster RCNN

Leaf diseases are a common disease in many plants. It has been normally controlled by fungicides bactericides and resistant varieties. Leaves are important for the fast-growing of plants and to extend the production of crops. But in this paper, predominantly engrossed in peanut plant leaves. Nowadays, India is the largest producer of groundnut in the world but when it comes to production, the average yields at 745kg/ha. Whereas disease attack is the foremost reason for the low yield. However, identifying diseases in plant leaves is profound challenging for farmers in day-to-day life. To address the respective challenge, a leaf disease detection system based on Machine Learning (ML) and viable Faster Region-Based Convolutional Neural Networks (RCNN) algorithms has been proposed. This result reveals that the RCNN provides a solution to whether the leaf is in a fine or infirmity position. Moreover, the proposed model has been analyzed concerning the accuracy, time complexity, and computational complexity.