GIT: A Transformer-Based Deep Learning Model for Geoacoustic Inversion

Geoacoustic inversion is a challenging task in marine research due to the complex environment and acoustic propagation mechanisms. With the rapid development of deep learning, various designs of neural networks have been proposed to solve this issue with satisfactory results. As a data-driven method...

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Bibliografske podrobnosti

Principais autores:	Sheng Feng, Xiaoqian Zhu, Shuqing Ma, Qiang Lan
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2023-05-01
Serija:	Journal of Marine Science and Engineering
Teme:	geoacoustic inversion deep learning transformer model 2-D positional embedding
Online dostop:	https://www.mdpi.com/2077-1312/11/6/1108
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