@inproceedings{647f75c253384779bd8c0cbbf199e031,
title = "Object Recognition Through UAV Observations Based on Yolo and Generative Adversarial Network",
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.",
keywords = "Machine learning, Object recognition, UAV",
author = "Bo Li and Zhigang Gan and Neretin, \{Evgeny Sergeevich\} and Zhipeng Yang",
note = "Publisher Copyright: {\textcopyright} 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 6th EAI International Conference on IoT as a Service, IoTaaS 2020 ; Conference date: 19-11-2020 Through 20-11-2020",
year = "2021",
doi = "10.1007/978-3-030-67514-1\_35",
language = "英语",
isbn = "9783030675134",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "439--449",
editor = "Bo Li and Changle Li and Mao Yang and Zhongjiang Yan and Jie Zheng",
booktitle = "IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings",
}