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Artificial intelligence guides rapid data-driven exploration of underwater habitats

人工智能指导水下栖息地的快速数据驱动探索

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来源:
EurekAlert
全文链接1:
https://www.eurekalert.org/pub_releases/2018-08/soi-aig082918.php
全文链接2:
类型:
前沿资讯
语种:
英文
原文发布日期:
摘要:
A recent expedition led by Dr. Blair Thornton, holding Associate Professorships at both the University of Southampton and the Institute of Industrial Science, the University of Tokyo, demonstrated how the use of autonomous robotics and artificial intelligence at sea can dramatically accelerate the exploration and study of hard to reach deep sea ecosystems, like intermittently active methane seeps. Thanks to rapid high throughput data analysis at sea, it was possible to identify biological hotspots at the Hydrate Ridge Region off the coast of Oregon, quickly enough to survey and sample them, within days following the Autonomous Underwater Vehicles (AUV) imaging survey. The team aboard research vessel Falkor used a form of Artificial Intelligence, unsupervised clustering, to analyze AUV-acquired seafloor images and identify target areas for more detailed photogrammetric AUV surveys and focused interactive hotspot sampling with ROV SuBastian.
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