一种深度学习模型,用于检测流域声学断层扫描系统中弱水下信号的到达时间

Weicong Zheng1, Xiaojian Yu2, Xuming Peng3,4,5

  • 1School of Information, Xiamen University, Xiamen 361102, China.

PubMed
概括

一个新的深度学习模型,DCA-Net,在具有挑战性的水下条件下准确地检测声信号到达时间. 这一进步提高了流域声学断层扫描 (FAT) 系统的性能,即使信号噪声比 (SNR) 非常低.

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