ANALYSIS OF DISEASE DETECTION IN COTTON PLANT LEAVES USING CONVOLUTIONAL NEURAL NETWORKS.

Abstract

Cotton (Gossypium spp.) is a vital crop that contributes significantly to global textile and oil seed industries. However, cotton cultivation faces considerable challenges due to various diseases affecting its leaves. The accurate and timely detection of diseases in cotton plant leaves is of paramount importance for ensuring optimal crop health and maximizing agricultural productivity. The CNN model was trained using a dataset that contained 10,000 leaf images, representing three diseases and healthy samples. The model was successful in detecting these diseases with a 98% accuracy rate.