Abstract: Locust is the stubborn pest insects which can damage crops and ecosystems.Traditional methods for monitoring locust have many disadvantages.To effectively apply massive field image data to achieve real-time monitoring of locusts, a locust automatic identification model based on a deep learning network was established in this study.Firstly, 280 locust RGB images photographed by the mobile phone camera in a complex field environment from the grasslands of Xilinhot, Inner Mongolia were obtained.Then the Faster R-CNN network structure which performs better in recognition was used.The accuracy of this model is 0.756.The model performs well on locust detection and outperforms the previous methods in the identify results and practicality.The model can accurately identify the locust from the complex environment on fields, which provide auxiliary information for the control of locusts.It is a basis for establishing a real-time monitoring system for monitoring locusts.At the same time, the network structure can also be applied to other pests and diseases' monitor.In addition, the model broadens the application field of deep learning algorithms.