Apple Leaf Disease Identification and Classification using ResNet Models

Abstract

With the development and popularization of intelligent agricultural system, more and more research and attention have been paid to the detection and identification of leaf diseases. We used data sets of apple grey-spot disease, black star disease, cedar rust disease and healthy leaves to study the identification and classification of apple leaf diseases. Image segmentation SVM classifier and ResNet and VGG convolutional neural network model were used for comparison and improvement. In the final experiment, ResNet-18 with fewer layers of ResNet obtained an accuracy rate of 98.5% achieving better recognition effects.