Aerial target recognition based on convolutional neural network

Ziqi Liu; Yuanyuan Xu

doi:10.1117/12.2673656

22 May 2023 Aerial target recognition based on convolutional neural network

Ziqi Liu, Yuanyuan Xu

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126401A (2023) https://doi.org/10.1117/12.2673656
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

In the aerospace field, in the process of identifying and tracking air targets, it is faced with inaccurate or incomplete target recognition. This research is based on the auxiliary analysis and recognition capabilities of deep learning convolutional neural networks to realize the recognition of aerial targets, so as to improve the recognition accuracy and reduce the recognition error rate. Take the aircraft data provided by the Institute of Aeronautics and Astronautics as the research object, perform image preprocessing on it, build the aircraft data set, build a network framework using python language in the TensorFlow environment, and perform recognition training on the model, and finally test the trained model and result analysis.

Citation Download Citation

Ziqi Liu and Yuanyuan Xu "Aerial target recognition based on convolutional neural network", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126401A (22 May 2023); https://doi.org/10.1117/12.2673656

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