文章基本信息

标题：A Vehicle Detection Method for Aerial Image Based on YOLO
本地全文：下载
作者：Junyan Lu ; Chi Ma ; Li Li 等
期刊名称：Journal of Computer and Communications
印刷版ISSN：2327-5219
电子版ISSN：2327-5227
出版年度：2018
卷号：6
期号：11
页码：98-107
DOI：10.4236/jcc.2018.611009
语种：English
出版社：Scientific Research Publishing
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.
关键词：Vehicle Detection;Aerial Image;YOLO;VEDAI;COWC;DOTA