Underwater Acoustic Target Recognition Based on Dual Attention Networks and Multiresolution Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Underwater Acoustic Target Recognition Based on Dual Attention Networks and Multiresolution Convolutional Neural Networks

Published:2021-09-20 Issue: Volume: Page:
ISSN:
Container-title:OCEANS 2021: San Diego – Porto
language:
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Author:

Liu Chengwei¹,Hong Feng¹,Feng Haihong¹,Hu Menglu¹

Affiliation:

1. Shanghai acoustics lab Chinese Academy of Sciences,ChinaShanghai,China

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9705657/9705658/09706009.pdf?arnumber=9706009

Reference20 articles.

1. Ship Type Classification by Convolutional Neural Networks with Auditory-Like Mechanisms

2. Underwater target recognition using convolutional recurrent neural networks with 3-D Mel-spectrogram and data augmentation

3. Underwater Acoustic Target Recognition with a Residual Network and the Optimized Feature Extraction Method

4. An Underwater Acoustic Target Recognition Method Based on Restricted Boltzmann Machine

5. Environment Sound Classification Using a Two-Stream CNN Based on Decision-Level Fusion

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1. Artificial Intelligence-Based Underwater Acoustic Target Recognition: A Survey;Remote Sensing;2024-09-08

2. An Underwater Acoustic Target Recognition Method Based on Transfer Learning;2024 9th International Conference on Electronic Technology and Information Science (ICETIS);2024-05-17

3. Design of a Deep Learning-Based Underwater Acoustic Sensor Transceiver;IEEE Sensors Journal;2024-03-15

4. An Explainable ML Model for MultiClass Marine Vessel Classification Using Passive Sonar Signals;2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT);2024-03-15

5. Self-Supervised Learning-For Underwater Acoustic Signal Classification With Mixup;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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