Development of an Automated Seafloor Hydrothermal Signal Detection System from Shipborne MBES Data Using Deep Learning

Kosei Yamashiro

Presentation information

[E] Oral

H (Human Geosciences ) » H-RE Resource and Engineering Geology

[H-RE12] Seafloor mineral resources and their natural analogues on land

Thu. May 28, 2026 3:30 PM - 5:00 PM Exhibition Hall Special Setting (3) (Exhibition Hall 7&8, Makuhari Messe)

Chairperson:Jamieson William John(University of Ottawa), Martin Jonathan Andrew(University of Nevada, Las Vegas), Seo Jung Hun(School of Earth and Environmental Sciences, Seoul National University)

4:30 PM - 4:45 PM

[HRE12-10] Development of an Automated Seafloor Hydrothermal Signal Detection System from Shipborne MBES Data Using Deep Learning

*Kosei Yamashiro¹, Kazuhide Mimura², Kentaro Nakamura^1,3, Kazutaka Yasukawa¹, Yasuhiro Kato^1,3 (1. School of Engineering, The University of Tokyo, 2. National Institute of Advanced Industrial Science and Technology, 3. Ocean Resources Research Institute for Next Generation, Chiba Institute of Technology)

Keywords:Seafloor Hydrothermal Deposit, Deep Learning, Object Detection, MBES(multi-beam echo sounder), Time Series Analysis