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Interpretable features for underwater acoustic target recognition
Measurement, 2021Abstract The major challenge of underwater acoustic target recognition is that the features clearly characterizing the underwater acoustic targets remain indistinct, where the sound signals are often submerged by intense noise. In this paper, we aim to discover an efficient interpretable feature set that can reveal the inherent mechanism, and result ...
Junjun Jiang +4 more
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Union-Domain Knowledge Distillation for Underwater Acoustic Target Recognition
IEEE Transactions on Geoscience and Remote SensingUnderwater acoustic target recognition (UATR) can be significantly empowered by advancements in deep learning (DL). However, the effectiveness of DL-based UATR methods is often constrained by the limited computing resources available on underwater ...
Xiaohui Chu +5 more
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Time-Series Acoustic Network for Underwater Acoustic Target Recognition
2025 IEEE International Conference on Multimedia and Expo (ICME)Underwater acoustic target recognition traditionally relies on feature engineering, wherein features are extracted through time-frequency transformations and fed into classifiers for target recognition. However, the noise distribution is uneven and lacks
Pengyuan Qi, Ye Tian, Guisheng Yin
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Unlabeled Samples Improve Few-Shot Underwater Acoustic Target Recognition
IEEE Transactions on Geoscience and Remote SensingThe complex underwater environments pose major challenges to acoustic target recognition with insufficient labeled samples and mismatched domain issues. Although current few-shot learning (FSL) methods could alleviate the data scarcity problem, yet they ...
Zhuofan He +5 more
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Domain-adaptive meta learning for underwater acoustic target recognition
The Journal of the Acoustical Society of AmericaThis study provides a unique opportunity for advancements in underwater acoustic target recognition (UATR). The ShipsEar dataset, comprised of underwater acoustic recordings captured by hydrophones across eight distinct locations, encapsulates diverse environmental conditions and vessel sound characteristics.
Junho Bae, Wooyoung Hong, Youngmin Choo
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Underwater Acoustic Target Recognition Using Software Defined Radio
2023 46th International Conference on Telecommunications and Signal Processing (TSP), 2023One of the important results of ship movement is acoustics noise which contains a lot of ship attributes. With developing technology, the classification of targets problem remains important. Recognition of ships is possible using ships' acoustic trace data.
İlhan, Hacı, Pehlivan, Adil Ugur
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Underwater Acoustic Target Recognition on ShipsEar Dataset
2023The task of classifying underwater audio source has various marine-oriented applications, including maritime and environmental monitoring, detection of marine life, and underwater surveillance. However, Underwater Acoustic Target Recognition (UATR) remains challenging due to several factors.
Tam Phi, David Han
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Underwater acoustic targets recognition algorithm based on NMF
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2020To solve the problem of low recognition rate of underwater targets for the reason of their large feature discreteness within class and high feature overlapping between classes, the underwater targets recognition algorithm based on NMF universal dictionary model (UDM) is proposed, in which, the UDM is established using the existing underwater acoustic ...
Xiaoqing Zheng +3 more
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A Transformer-Based Deep Learning Network for Underwater Acoustic Target Recognition
IEEE Geoscience and Remote Sensing Letters, 2022Underwater acoustic target recognition (UATR) is usually difficult due to the complex and multipath underwater environment. Currently, deep-learning (DL)-based UATR methods have proved their effectiveness and have outperformed the traditional methods by ...
Sheng Feng, Xiaoqian Zhu
semanticscholar +1 more source