Identification of Soybean Leaf Spot Diseases using Deep Convolutional Neural Networks

Abstract

In this paper, we designed a Deep Convolutional Neural Network based on LeNet to perform soybean leaf spot disease recognition and classification using affected areas of disease spots. The affected areas of disease spots were segmented from the leaves images using the Unsupervised fuzzy clustering algorithm. The proposed Deep Convolutional Neural Network model achieved a testing accuracy of 89.84%, and poor per class recognition results in 1378 images misclassified, and 1271 images correct classified. TheVGG16 achieved the best performance reaching a 93.54% success rate, and better per class recognition results in 1245 images misclassified, and 1404 images correct classified. Keywords-Deep convolutional neural network, Unsupervised fuzzy clustering algorithm, image segmentation, soybean leaf spot diseases.