Underwater acoustic target recognition using RCRNN and wavelet-auditory feature
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17406-2.pdf
Reference55 articles.
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4. Biswas M, Rahaman S, Ahmadian A et al. (2022) Automatic spoken language identification using mfcc based time series features. Multimed Tools Appl 1–31
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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Artificial Intelligence-Based Underwater Acoustic Target Recognition: A Survey;Remote Sensing;2024-09-08
2. A Novel Multi-Feature Fusion Model Based on Pre-Trained Wav2vec 2.0 for Underwater Acoustic Target Recognition;Remote Sensing;2024-07-03
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