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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep convolution stack for waveform in underwater acoustic target recognition
Shengzhao Tian, Duanbing Chen, Hang Wang, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

A Survey of Underwater Acoustic Target Recognition Methods Based on Machine Learning
Xinwei Luo, Lu Chen, Hanlu Zhou, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 2, pp. 384-384
Open Access | Times Cited: 32
A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance
Lucas C. F. Domingos, Paulo E. Santos, Phillip S. M. Skelton, et al.
Sensors (2022) Vol. 22, Iss. 6, pp. 2181-2181
Open Access | Times Cited: 33
Joint learning model for underwater acoustic target recognition
Shengzhao Tian, Duanbing Chen, Yan Fu, et al.
Knowledge-Based Systems (2022) Vol. 260, pp. 110119-110119
Open Access | Times Cited: 31
Underwater acoustic target recognition based on spectrum component analysis of ship radiated noise
Pengsen Zhu, Yonggang Zhang, Yulong Huang, et al.
Applied Acoustics (2023) Vol. 211, pp. 109552-109552
Closed Access | Times Cited: 21
Data augmentation method for underwater acoustic target recognition based on underwater acoustic channel modeling and transfer learning
Daihui Li, Feng Liu, Tongsheng Shen, et al.
Applied Acoustics (2023) Vol. 208, pp. 109344-109344
Closed Access | Times Cited: 17
A Lightweight Network Model Based on an Attention Mechanism for Ship-Radiated Noise Classification
Shuang Yang, Xue Lingzhi, Xi Hong, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 2, pp. 432-432
Open Access | Times Cited: 16
Present status and challenges of underwater acoustic target recognition technology: A review
Zhufeng Lei, Lei Xiaofang, Na Wang, et al.
Frontiers in Physics (2022) Vol. 10
Open Access | Times Cited: 26
A Novel Deep-Learning Method with Channel Attention Mechanism for Underwater Target Recognition
Xue Lingzhi, Xiangyang Zeng, Anqi Jin
Sensors (2022) Vol. 22, Iss. 15, pp. 5492-5492
Open Access | Times Cited: 22
Self-supervised learning–based underwater acoustical signal classification via mask modeling
Kele Xu, Qisheng Xu, Kang Soo You, et al.
The Journal of the Acoustical Society of America (2023) Vol. 154, Iss. 1, pp. 5-15
Closed Access | Times Cited: 13
Mobile_ViT: Underwater Acoustic Target Recognition Method Based on Local–Global Feature Fusion
Haiyang Yao, Tian Gao, Yong Wang, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 4, pp. 589-589
Open Access | Times Cited: 5
A survey on machine learning in ship radiated noise
Hilde I. Hummel, Rob van der Mei, Sandjai Bhulai
Ocean Engineering (2024) Vol. 298, pp. 117252-117252
Open Access | Times Cited: 4
Underwater Acoustic Target Classification using Auditory Fusion Features and Efficient Convolutional Attention Network
Junjie Yang, Zhenyu Zhang, Wei Li, et al.
IEEE Sensors Letters (2025) Vol. 9, Iss. 3, pp. 1-4
Closed Access
Adaptive underwater acoustic target recognition based on multi-scale residual and attention mechanism
Jingyi Wang, Peng Qian, Yingxuan Chen, et al.
Digital Signal Processing (2025), pp. 105193-105193
Closed Access
MSLEFC: A low-frequency focused underwater acoustic signal classification and analysis system
Yunqi Zhang, Qunfeng Zeng
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106333-106333
Closed Access | Times Cited: 11
Underwater acoustic target recognition method based on a joint neural network
Xing Cheng Han, Chenxi Ren, Liming Wang, et al.
PLoS ONE (2022) Vol. 17, Iss. 4, pp. e0266425-e0266425
Open Access | Times Cited: 18
A Lightweight Network Based on Multi-Scale Asymmetric Convolutional Neural Networks with Attention Mechanism for Ship-Radiated Noise Classification
Chenhong Yan, Shefeng Yan, Tianyi Yao, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 1, pp. 130-130
Open Access | Times Cited: 3
Underwater sound classification using learning based methods: A review
Muhammad Azeem Aslam, Lefang Zhang, Xin Liu, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124498-124498
Open Access | Times Cited: 3
Active Underwater Target Detection Using a Shallow Neural Network With Spectrogram-Based Temporal Variation Features
Youngmin Choo, Keunhwa Lee, Wooyoung Hong, et al.
IEEE Journal of Oceanic Engineering (2022) Vol. 49, Iss. 1, pp. 279-293
Closed Access | Times Cited: 13
An attention-based multi-scale convolution network for intelligent underwater acoustic signal recognition
Aolong Zhou, Xiaoyong Li, Wen Zhang, et al.
Ocean Engineering (2023) Vol. 287, pp. 115784-115784
Closed Access | Times Cited: 7
An Investigation of Preprocessing Filters and Deep Learning Methods for Vessel Type Classification With Underwater Acoustic Data
Lucas C. F. Domingos, Paulo E. Santos, Phillip S. M. Skelton, et al.
IEEE Access (2022) Vol. 10, pp. 117582-117596
Open Access | Times Cited: 11
Deep Learning Based Underwater Acoustic Target Recognition: Introduce a Recent Temporal 2D Modeling Method
Jun Tang, Wenbo Gao, Enxue Ma, et al.
Sensors (2024) Vol. 24, Iss. 5, pp. 1633-1633
Open Access | Times Cited: 1
分布式光纤水听器技术研究和应用进展
王照勇 Wang Zhaoyong, 刘依凡 Liu Yifan, 陈义赐 Chen Yici, et al.
Acta Optica Sinica (2024) Vol. 44, Iss. 1, pp. 0106004-0106004
Open Access | Times Cited: 1
Deep Learning Based Classification of Underwater Acoustic Signals
Faiyaz Ahmad, Mohd Zeeshan Ansari, Ramsha Anwar, et al.
Procedia Computer Science (2024) Vol. 235, pp. 1115-1124
Open Access | Times Cited: 1
A Robust Feature Extraction Method for Underwater Acoustic Target Recognition Based on Multi-Task Learning
Daihui Li, Feng Liu, Tongsheng Shen, et al.
Electronics (2023) Vol. 12, Iss. 7, pp. 1708-1708
Open Access | Times Cited: 4
Differential treatment for time and frequency dimensions in mel-spectrograms: An efficient 3D Spectrogram network for underwater acoustic target classification
Ning Tang, Fei Zhou, Yan Wang, et al.
Ocean Engineering (2023) Vol. 287, pp. 115863-115863
Closed Access | Times Cited: 4
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