A self-supervised dual-channel self-attention acoustic encoder for underwater acoustic target recognition

• Main Authors: WANG, Xingmei, WU, Peiran, LI, Boquan, ZHAN, Ge, LIU, Jinghan, LIU, Zijian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Dual-channel mechanism; Local self-attention; Self-supervised learning; Underwater acoustic target recognition; Artificial Intelligence and Robotics; Oceanography and Atmospheric Sciences and Meteorology
• Online Access: https://ink.library.smu.edu.sg/sis_research/8738
• Institution: Singapore Management University

Due to the considerable noise and high annotation cost of passive sonar acquisition data challenges, underwater acoustic target recognition (UATR) tasks require novel solutions. In this paper, we propose a self-supervised dual-channel self-attention acoustic encoder (DSAE) for UATR tasks. First, to...