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Haiyang Yao, Tian Gao, Yong Wang, Haiyan Wang and Xiao Chen
To overcome the challenges of inadequate representation and ineffective information exchange stemming from feature homogenization in underwater acoustic target recognition, we introduce a hybrid network named Mobile_ViT, which synergizes MobileNet and Tr...
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Xiaodong Cui, Zhuofan He, Yangtao Xue, Keke Tang, Peican Zhu and Jing Han
Underwater Acoustic Target Recognition (UATR) plays a crucial role in underwater detection devices. However, due to the difficulty and high cost of collecting data in the underwater environment, UATR still faces the problem of small datasets. Few-shot le...
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Fang Ji, Junshuai Ni, Guonan Li, Liming Liu and Yuyang Wang
Underwater acoustic target recognition methods based on time-frequency analysis have shortcomings, such as missing information on target characteristics and having a large computation volume, which leads to difficulties in improving the accuracy and imme...
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Jianjing Deng, Xiangfeng Yang, Liwen Liu, Lei Shi, Yongsheng Li and Yunchuan Yang
Underwater acoustic homing weapons (UAHWs) are formidable underwater weapons with the capability to detect, identify, and rapidly engage targets. Swift and precise target identification is crucial for the successful engagement of targets via UAHWs. This ...
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Anqi Jin and Xiangyang Zeng
Long-range underwater targets must be accurately and quickly identified for both defense and civil purposes. However, the performance of an underwater acoustic target recognition (UATR) system can be significantly affected by factors such as lack of data...
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Shuang Yang, Lingzhi Xue, Xi Hong and Xiangyang Zeng
Recently, deep learning has been widely used in ship-radiated noise classification. To improve classification efficiency, avoiding high computational costs is an important research direction in ship-radiated noise classification. We propose a lightweight...
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Qiankun Yu, Min Zhu, Wen Zhang, Jian Shi and Yan Liu
Sound source recognition is a very important application of passive sonar. How to distinguish between surface and underwater acoustic sources has always been a challenge. Due to the mixing of underwater target radiated noise and marine environmental nois...
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Dali Liu, Wenhao Shen, Wenjing Cao, Weimin Hou and Baozhu Wang
The acquisition of target data for underwater acoustic target recognition (UATR) is difficult and costly. Although deep neural networks (DNN) have been used in UATR, and some achievements have been made, the performance is not satisfactory when recognizi...
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Jie Chen, Bing Han, Xufeng Ma and Jian Zhang
Underwater target recognition is an important supporting technology for the development of marine resources, which is mainly limited by the purity of feature extraction and the universality of recognition schemes. The low-frequency analysis and recording...
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Xinwei Luo, Minghong Zhang, Ting Liu, Ming Huang and Xiaogang Xu
This paper focuses on the automatic target recognition (ATR) method based on ship-radiated noise and proposes an underwater acoustic target recognition (UATR) method based on ResNet. In the proposed method, a multi-window spectral analysis (MWSA) method ...
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