Research on Unmanned Vessel Surface Object Detection Based on Fusion of SSD and Faster-RCNN

被引：0
|
作者：
Song, Xueqiang [1 ]
Jiang, Peng [1 ]
Zhu, He [2 ]
机构：
[1] Hangzhou Dianzi Univ, Hangzhou, Peoples R China
[2] Asea Brown Boveri Ltd, Hangzhou, Peoples R China
来源：
2019 CHINESE AUTOMATION CONGRESS (CAC2019) | 2019年
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
object detection; SSD; Faster-RCNN; Kalman filtering; Unmanned Surface Vehicle (USV);
D O I：
10.1109/cac48633.2019.8997431
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a real-time obstacle detection algorithm for obstacle detection on the sea surface for Unmanned Surface Vehicle (USV). The algorithm uses Kalman filtering to fuse SSD and Faster-RCNN model.Simulation tests have been taken and shown that compared with the traditional algorithm, this algorithm can significantly improve the speed,stability and accuracy.
引用
收藏
页码：3784 / 3788
页数：5
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