Automated Detection of Hydrothermal Emission Signatures From Multibeam Echo Sounder Images Using Deep Learning

Seafloor massive sulfide deposits have attracted attention as a mineral resource, as they contain a wide variety of base, precious, and other valuable critical metals. Previous studies have shown that signatures of hydrothermal activity can be detected by a multibeam echo sounder (MBES), which would...

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Bibliographic Details

Published in:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Main Authors:	Kazuhide Mimura, Kentaro Nakamura, Kazuhiro Takao, Kazutaka Yasukawa, Yasuhiro Kato
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Subjects:	Deep learning massive sulfide deposits multibeam echo sounder (MBES) object detection seafloor exploration seafloor mineral resource
Online Access:	https://ieeexplore.ieee.org/document/10052641/