Corn Leaf Disease Detection Using Genetic Algorithm and Weighted Voting

Corn production in India holds the country GDP up to 18%. Every year in India the farmers cultivate corn around twenty-two million tons. So, in the field of agriculture and in the era of modern computing the identification of infected leaves plays the major role. The proposed system is designed in such way that it helps the farmers to detect the Corn leave infection early and to increase the production of crop the scientific approach is given. The important objective of the paper is to give an efficient and accurate Deep Learning algorithm for the detection of infected leaf. So, the Deep Learning models like Sequential 2-Dimentional model and Dense Net model is used and the Ensemble Learning techniques like Weighted voting is used and obtained the accuracy of 98%.