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
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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