TITLE:
A Vehicle Detection Method for Aerial Image Based on YOLO
AUTHORS:
Junyan Lu, Chi Ma, Li Li, Xiaoyan Xing, Yong Zhang, Zhigang Wang, Jiuwei Xu
KEYWORDS:
Vehicle Detection, Aerial Image, YOLO, VEDAI, COWC, DOTA
JOURNAL NAME:
Journal of Computer and Communications,
Vol.6 No.11,
November
19,
2018
ABSTRACT:
With the application of UAVs in intelligent transportation systems, vehicle detection for aerial images has become a key engineering technology and has academic research significance. In this paper, a vehicle detection method for aerial image based on YOLO deep learning algorithm is presented. The method integrates an aerial image dataset suitable for YOLO training by pro-cessing three public aerial image datasets. Experiments show that the training model has a good performance on unknown aerial images, especially for small objects, rotating objects, as well as compact and dense objects, while meeting the real-time requirements.