Results 21 to 30 of about 20,770 (204)

Underwater acoustic target recognition under working conditions mismatch

Xibei Gongye Daxue Xuebao
The working conditions of the ship will have a great impact on the radiated noise of the ship. Even if the same ship is traveling in the same sea area, different working conditions will produce different radiated noise, thus affecting the accuracy of ...
WANG Haitao, JIN Anqi, YANG Shuang, ZENG Xiangyang   +3 more
doaj   +2 more sources

An efficient deep learning approach with frequency and channel optimization for underwater acoustic target recognition. [PDF]

Sci Rep
Ship radiated noise (SRN) recognition is challenging due to environmental noise and the broad frequency range of underwater signals. Existing deep learning models often include irrelevant frequencies and use red, green, and blue (RGB) channel ...
Zeng D, Yan S, Yang J, Pan X.
europepmc   +2 more sources

Enhancing Underwater Acoustic Target Recognition Through Advanced Feature Fusion and Deep Learning

Journal of Marine Science and Engineering
Underwater Acoustic Target Recognition (UATR) is critical to maritime traffic management and ocean monitoring. However, underwater acoustic analysis is fraught with difficulties.
Yanghong Zhao, Guohao Xie, Haoyu Chen, Mingsong Chen, Li Huang   +4 more
doaj   +2 more sources

Underwater Acoustic Target Recognition: A Combination of Multi-Dimensional Fusion Features and Modified Deep Neural Network

Remote Sensing, 2019
A method with a combination of multi-dimensional fusion features and a modified deep neural network (MFF-MDNN) is proposed to recognize underwater acoustic targets in this paper.
Xingmei Wang, Anhua Liu, Yu Zhang, Fuzhao Xue   +3 more
doaj   +3 more sources

The Underwater Acoustic Target Recognition Algorithm Based on Evidence Clustering [PDF]

Xibei Gongye Daxue Xuebao, 2018
In underwater acoustic target recognition, the target signal is usually complex and the samples which are difficult to obtain also have some uncertain information.
Yang Zhang, Jianhua Yang, Hong Hou
doaj   +2 more sources

Cross-Domain Contrastive Learning-Based Few-Shot Underwater Acoustic Target Recognition

Journal of Marine Science and Engineering
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.
Xiaodong Cui, Zhuofan He, Yangtao Xue, Keke Tang, Peican Zhu, Jing Han   +5 more
doaj   +2 more sources

Neural Edge Histogram Descriptors for Underwater Acoustic Target Recognition

OCEANS 2025 Brest
6 pages, 5 figures.
Agashe, Atharva, Carreiro, Davelle, Van Dine, Alexandra, Peeples, Joshua   +3 more
openaire   +3 more sources

Efficient One-Dimensional Network Design Method for Underwater Acoustic Target Recognition

Journal of Marine Science and Engineering
Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets.
Qing Huang, Xiaoyan Zhang, Anqi Jin, Menghui Lei, Mingmin Zeng, Peilin Cao, Zihan Na, Xiangyang Zeng   +7 more
doaj   +2 more sources

Graph Embedding with Mel-spectrograms for Underwater Acoustic Target Recognition

IEEE Journal of Oceanic Engineering
Underwater acoustic target recognition (UATR) is extremely challenging due to the complexity of ship-radiated noise and the variability of ocean environments. Although deep learning (DL) approaches have achieved promising results, most existing models implicitly assume that underwater acoustic data lie in a Euclidean space. This assumption, however, is
Feng, Sheng, Ma, Shuqing, Zhu, Xiaoqian
openaire   +3 more sources

Model for Underwater Acoustic Target Recognition with Attention Mechanism Based on Residual Concatenate

Journal of Marine Science and Engineering, 2023
Underwater acoustic target recognition remains a formidable challenge in underwater acoustic signal processing. Current target recognition approaches within underwater acoustic frameworks predominantly rely on acoustic image target recognition models ...
Zhe Chen, Guohao Xie, Mingsong Chen, Hongbing Qiu   +3 more
doaj   +1 more source