Study on Plant Diseases and Insect Pests Recognition Based on Deep Learning

Distinguishing between different diseases and insect pests that affect maize crops is difficult. Therefore, in this study, a maize disease and pest database was established to train the AlexNet, VGG16, and ResNet50 deep convolutional neural network models. After training, these models were used to identify different types of diseases via the identification of disease indicators in local images. The test results showed that the validation set recognition accuracies of the AlexNet, VGG16, and ResNet50 models were 86.98%, 87.70%, and 85.98%, respectively. Compared with the traditional method, the recognition accuracy of the proposed method was superior. This result provides a strong basis for pest control work via a real-time and accurate technique for identifying agricultural pests. © (2025), (International Association of Engineers). All rights reserved.