基于分布式计算的三维多波束测深数据处理。在安全航行中降低虚警和无监督水下目标识别中的应用

G. Matte, F. Chaillan, A. Heinzle
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引用次数: 0

摘要

本研究的目标是利用人工智能(AI)算法和分布式计算生态系统来增强3d多波束回声测深仪的数据处理功能。我们首先考虑后处理案例,在海试期间记录了完整的数据集。因此,我们建议的框架设计用于大量真实世界的数据处理,允许使用假警报减少和水下目标识别技术,这可以很容易地用作水下自主车辆安全导航的决策。
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3D Multibeam Echo Sounder Data Processing Using Distributed Computing. Application To False Alarm Reduction And Unsupervised Underwater Object Recognition For Safe Navigation
The goal of this study is to take advantage of artificial intelligence (AI) algorithms and distributed computing ecosystem to enhance the 3D-multibeam echo sounder data processing functionality. We consider first the post processing case, where a complete dataset has been recorded during sea trials. Hence, our suggested framework designed for massive real world data processing allows employing false alarm reduction and underwater object recognition techniques, which can be easily used as decision making for underwater autonomous vehicle safe navigation.
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