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OpenSARShip 2.0: A large-volume dataset for deeper interpretation of ship targets in Sentinel-1 imagery

机译:OpenSARShip 2.0:海量数据集,可对Sentinel-1影像中的船只目标进行更深入的解释

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In the era of big data for synthetic aperture radar (SAR), multiple SAR systems have come into service, including Sentinel-1. The support of large-volume datasets is the key to the deep interpretation of ship targets in Sentinel-1 imagery. In this paper, we present OpenSARShip 2.0, the newest and upgraded version of OpenSARShip, which is dedicated to the deeper interpretation of SAR imagery for marine surveillance. Based on the higher requirements for ship target interpretation, the OpenSARShip 2.0, covering 34528 SAR ship chips with automatic identification system (AIS) information, possesses three improvements: large volume, interference labeling, and type levels, which are described in this paper. In addition, an application case involving the geometric parameter extraction is introduced to demonstrate the applicability of the large dataset.
机译:在合成孔径雷达(SAR)的大数据时代,已经有多个SAR系统投入使用,包括Sentinel-1。对大量数据集的支持是在Sentinel-1图像中深入解释舰船目标的关键。在本文中,我们将介绍OpenSARShip 2.0,它是OpenSARShip的最新和升级版本,致力于深入理解用于海洋监视的SAR图像。基于对船舶目标解释的更高要求,OpenSARShip 2.0涵盖了34528个具有自动识别系统(AIS)信息的SAR船舶芯片,具有三个改进:大容量,干扰标记和类型级别,本文将对此进行介绍。此外,介绍了涉及几何参数提取的应用案例,以证明大型数据集的适用性。

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