Results 151 to 160 of about 20,770 (204)

Clairaudience: a lightweight attentional residual neural network with data augmentation and feature fusion for underwater acoustic target recognition

Computer/law journal
Marine engineering has boomed and many deep learning-based methods have been proposed for underwater acoustic target recognition. However, most of these methods are dedicated to develop more complex convolutional neural networks to achieve better ...
Jing Li, Yucheng Han, Xudong Wang, Xinglong Zhang, Lili Zhang, Wei Wei, Pei Yu, Hongxin Tan, Kang Yang   +8 more
semanticscholar   +1 more source

Underwater Acoustic Target Recognition Based on Multi-scale Residuals and Dual Attention Mechanism

2025 IEEE 7th International Conference on Communications, Information System and Computer Engineering (CISCE)
Aiming at the problems that traditional ship underwater acoustic target recognition methods are difficult to achieve high recognition accuracy and have low robustness in complex underwater environments, this paper proposes a target recognition model that
Hanqing Song, Haoqi Wang, Shuang Xiao, Yan Wang, Z. Zhong, Lei Yu, Mingguang Shan, Bin Liu   +7 more
semanticscholar   +1 more source

A Lightweight Fusion Model Based Jamba and Cross Fusion Mixture of Experts for Underwater Acoustic Target Recognition

IEEE Transactions on Aerospace and Electronic Systems
To alleviate the problems of low recognition accuracy and weak robustness in intelligent underwater acoustic target recognition systems, a lightweight fusion model based on the time and frequency attention module, MobileJiT, and cross fusion mixture of ...
Ming Chen, Feng Wang, Yangze Dong
semanticscholar   +1 more source

An Underwater Acoustic Target Recognition Method Based on Transfer Learning

2024 9th International Conference on Electronic Technology and Information Science (ICETIS)
 Underwater acoustic target recognition(UATR)is a challenging task Due to the high cost of sampling data, it is difficult to build a large-scale dataset.In this study,a new method based on transfer learning with a VGG16 model(Transfer-VGG16) is developed in which three-dimensional(3-D)data is used as the input.Use the dataset obtained in real scenarios
Xiaozhuo Yang, Huapeng Yu, Hanmin Sheng, Wenlong Zeng, Qingyuan He, Junyang Tu   +5 more
openaire   +1 more source

A momentum-based adversarial training approach for generalization in underwater acoustic target recognition: An individual-vessel perspective.

Journal of the Acoustical Society of America
Underwater passive acoustic recognition, which focuses on classifying targets based on ship-radiated noise, is a key challenge in underwater acoustics. Deep learning-based methods have gained popularity in recent years because of their strong performance.
Haotian Fang, Yuan Xie, Jiawei Ren, Wenchao Wang, Ji Xu   +4 more
semanticscholar   +1 more source

Underwater Acoustic Target Recognition Based on ReLU Gated Recurrent Unit

2020 6th International Conference on Robotics and Artificial Intelligence, 2020
In general, the traditional acoustic models'(e. g. Gaussian mixture model, GMM) for underwater acoustic target recognition (UATR) performance in sequential data has so far been disappointing. In contrast, Recurrent Neural Network (RNN) is a powerful tool for sequential data.
Xiaodong Sun, Xiaohan Yin, YaGuang Yin, Peishun Liu, Liang Wang, Ruichun Tang   +5 more
openaire   +1 more source

CA_MobileNetV2 for Underwater Acoustic Target Recognition

2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2023
Gao Tian, Yao Haiyang, Wang Haiyan, Wu Fan, Chen Xiao   +4 more
openaire   +1 more source

Adaptive Wavelet Transform Front End Integrated With Multitask Learning for Underwater Acoustic Target Recognition

IEEE Sensors Journal
Underwater acoustic target recognition (UATR) faces challenges from complex, nonstationary ship-radiated noise, which comprises a mixture of broadband, narrowband, and transient components requiring multiscale analysis. To address this, we propose an end-
Rongyao Zhao, Tongsheng Shen, Lyufang Zhao, Jiaru Chen, Jing Xu, Feng Liu   +5 more
semanticscholar   +1 more source

Multi-Task Attention Convolutional Neural Network for Underwater Acoustic Target Recognition in Few-shot Scenarios

2025 17th International Conference on Communication Software and Networks (ICCSN)
Underwater acoustic target recognition (UART) holds significant importance in fields such as rescue operations, national defense security, and marine biological research.
Shumeng Sun, Hao Zhang, Wei Huang, Zhenpeng Xu, Junpeng Lu, Yan Wang   +5 more
semanticscholar   +1 more source

Comparative Analysis of Deep Learning Techniques for Passive Underwater Acoustic Target Recognition: Overview, Challenges, and Future Directions

International Journal of Advanced Computer Science and Applications
—Passive underwater acoustic target recognition (UATR) involves analyzing acoustic waves captured by passive sonar to extract valuable information about submerged targets.
Song Yifei, Mohamad Farhan Mohamad Mohsin   +1 more
semanticscholar   +1 more source