Research Article
Object Recognition Through UAV Observations Based on Yolo and Generative Adversarial Network
@INPROCEEDINGS{10.1007/978-3-030-67514-1_35, author={Bo Li and Zhigang Gan and Evgeny Sergeevich Neretin and Zhipeng Yang}, title={Object Recognition Through UAV Observations Based on Yolo and Generative Adversarial Network}, proceedings={IoT as a Service. 6th EAI International Conference, IoTaaS 2020, Xi’an, China, November 19--20, 2020, Proceedings}, proceedings_a={IOTAAS}, year={2021}, month={1}, keywords={UAV Machine learning Object recognition}, doi={10.1007/978-3-030-67514-1_35} }- Bo Li
Zhigang Gan
Evgeny Sergeevich Neretin
Zhipeng Yang
Year: 2021
Object Recognition Through UAV Observations Based on Yolo and Generative Adversarial Network
IOTAAS
Springer
DOI: 10.1007/978-3-030-67514-1_35
Abstract
Aiming at the object recognition through UAV, an intelligent object recognition model based on YOLO and Generative adversarial network is proposed in this paper. Firstly, the solution is given, and an object recognition model that can realize intelligent recognition is established. Then, in order to improve the resolution of the identified images, an image resolution enhancement model based on generative adversarial networks is built. After that, the structure and parameters of the recognition model and image resolution enhancement model are adjusted through the simulation experiments to improve the accuracy and robustness of the object recognition. Finally, the object recognition model based on YOLO and generative adversarial network in this paper is verified through UAV.
