合成孔径雷达
计算机科学
隐蔽的
钥匙(锁)
探测器
目标检测
磁道(磁盘驱动器)
人工智能
计算机视觉
遥感
计算机安全
地理
电信
模式识别(心理学)
语言学
操作系统
哲学
作者
Mani Shankar Prasad,Shivani Verma,Yulia Shichkina
标识
DOI:10.1109/scm58628.2023.10159062
摘要
The robust detection of ships is one of the key techniques in coastal and marine applications of synthetic aperture radar (SAR). SAR images can be analysed for keeping a track on "dark vessels" used for Illegal, unreported, and unregulated (IUU) fishing. The term "dark vessel" typically refers to a ship that operates without transmitting its location or other identifying information, often with the intention of avoiding detection or surveillance. This can be for various reasons, such as for military, intelligence, or illegal activities. Smaller ships may be more manoeuvrable and able to operate in areas where larger ships may have difficulty navigating, making them potentially suitable for clandestine or covert operations. Thus, smaller ships can be referred to as "dark vessels" in certain contexts. This paper combines a well-established ship detection method (using CIFAR detector) with modern machine learning for classification (large_ship vs. small_ship) based on length estimation.
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