IR/EO ship detection and tracking using SiamMask

被引：0
|
作者：
Mame, Alnaasan [1 ]
Kim, Sungho [1 ]
机构：
[1] Yeungnam Univ, Dept Elect Engn, 280 Daehak Ro, Gyongsan 38541, South Korea
来源：
2022 22ND INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2022) | 2022年
基金：
新加坡国家研究基金会;
关键词：
Siammask; Ship tracking; Infrared; Deep learning; electro-optical; sensor fusion;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Ship detection and tracking in maritime remains a challenging task due to sea clutters, noise, huge deformation and low contrast. In this paper, we address the previous issue using Siammask framework with sensor fusion technique. In here, infrared sensor representations integrated with electro-optical sensor features through concatenation at feature level. Experimental results show that the overall process performs segmentation and tracking with a high-margin level exploiting multi-sensor features concatenation to compensate the loss of information in case of using single-sensor technique.
引用
收藏
页码：1604 / 1606
页数：3
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