Cotton Plant Fungal Disease Classification using Deep Learning Models

Grey mildew, Cercospora leaf spot, Alternaria leaf spot are the most common types of fungal leaf diseases of cotton plant. Accurate detection of cotton plant leaf diseases prevent the spreading of disease infection and ensure high production of cotton in industrial sector. The already existing computerized diagnostic systems are not guaranteed to produce accurate detection for cotton plant diseases. Deep learning models are developed to get high accuracy in prediction and classification of different cotton plant diseases. The performance of different deep learning models are evaluated on real time field cotton fungal disease dataset and compared to find out high accuracy model for the given dataset. The work proposed in this paper are carried out on cercospora leaf spot, grey mildew leaf images of cotton plant and experimental results presented that deep convolutional neural network models are more efficient for disease detection and classification as compared to traditional machine learning algorithms.