Advances and applications of machine learning in underwater acoustics
Haiqiang Niu,
Xiaolei Li,
Yonglin Zhang
et al.
Abstract:Recent advancements in machine learning (ML) techniques applied to underwater acoustics have significantly impacted various aspects of this field, such as source localization, target recognition, communication, and geoacoustic inversion. This review provides a comprehensive summary and evaluation of these developments. As a data-driven approach, ML played a pivotal role in discerning intricate relationships between input features and desired labels based on the provided training dataset. They are achieving suc… Show more
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