Lingfang Zhou
ABSTRACT
This study focuses on the development needs of smart ecological agriculture and proposes an improved network model based on ResNet50. The research aims to improve the accuracy and efficiency of automatic identification of corn pests and diseases. Firstly, the collected leaf data of corn pests and diseases were enhanced. The purpose of doing so is to expand the amount of data and achieve a balance between various types of data. Secondly, the size of the network convolution kernel was adjusted. And introduce SE attention mechanism to the backend of the network to optimize the effect of network detail feature extraction. Finally, through experimental verification, the results show that the network model has high accuracy and robustness in identifying corn pests and diseases, and can effectively improve the efficiency of corn pest control.
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