arXiv Machine Learning July 10, 2026 By Pierre-Yves Raumer, Axel Marmoret, Dorian Cazau, Anatole Gros-Martial, Richard Dreo, Maelle Torterotot, Sara Bazin, Flore Samaran, Jean-Yves Royer

A Self-Supervised Approach for Minimal-Annotation Hydroacoustic Data Exploration

Read the original on arXiv Machine Learning →

arXiv:2607. 07733v1 Announce Type: cross Abstract: Passive hydroacoustic monitoring often generates large volumes of continuous recordings that are only partially exploited due to the cost of manual annotation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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