Artificial intelligence technologies for Maritime Surveillance applications

被引：3

作者：

Fontana, Valerio ^{[1
]}

Blasco, Jose Manuel Delgado ^{[1
]}

Cavallini, Andrea ^{[1
]}

Lorusso, Nicola ^{[1
]}

Scremin, Alessandro ^{[1
]}

Romeo, Antonio ^{[1
]}

机构：

[1] RHEA Grp, Frascati, Italy

来源：

2020 21ST IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2020) | 2020年

关键词：

artificial intelligence; deep learning; convolutional networks; remote sensing; maritime surveillance; ship recognition; SAR; optical; environment; security; CNN;

D O I：

10.1109/MDM48529.2020.00067

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The use of AI methods is currently evolving tasks done in the past by image analysts. During the last years, technology had helped to jump into fully automatic methods for monitoring and surveillance tasks, such as object detection, change detection and many more. In this work we want to show some of the AI-based models which RHEA Group has been working on which can be applied to the maritime domain, such as ship detection and super-resolution of satellite data. Each of these models can be further extended and specialized into specific monitoring and surveillance tasks, from the detection of ghost ships, measure environmental damage or monitoring of critical infrastructure near harbors or protected areas. In this paper, we illustrate some examples of the status of our research activities and the developments of these prototype applications.

引用

页码：299 / 303

页数：5

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