A Vehicle Detection Method for Aerial Image Based on YOLO

• 作者: Chi Ma Jiuwei Xu Junyan Lu Li Li Xiaoyan Xing Yong Zhang Zhigang Wang
• 来源期刊: 电脑和通信(英文)
• 学科: 工学
• 关键词: VEHICLE DETECTION AERIAL IMAGE YOLO VEDAI COWC DOTA
• 年，卷（期）: 2018,（11）
• 页码范围: 98-107
• 页数: 10页
• 分类号: TP39

摘要

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.