Results 11 to 20 of about 20,770 (204)

STM: Spectrogram Transformer Model for Underwater Acoustic Target Recognition

Journal of Marine Science and Engineering, 2022
With the evolution of machine learning and deep learning, more and more researchers have utilized these methods in the field of underwater acoustic target recognition.
Peng Li, Ji Wu, Yongxian Wang, Qiang Lan, Wenbin Xiao   +4 more
doaj   +4 more sources

Hybrid local-global representation learning with stochastic Gaussian classification for underwater acoustic target recognition [PDF]

Scientific Reports
Underwater acoustic target recognition is critical for a broad spectrum of marine applications, yet its performance is often hindered by environmental variability, non-stationary propagation effects, and inherently low signal-to-noise ratio conditions ...
Cheng Yang, Qisheng Xu, Ming Feng, Hui Yang, Yulei Yuan, Yutao Dou, Junyi Zhao, Kele Xu   +7 more
doaj   +3 more sources

Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition. [PDF]

Sensors (Basel), 2018
Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples.
Yang H, Shen S, Yao X, Sheng M, Wang C.
europepmc   +4 more sources

Class-Incremental Learning-Based Few-Shot Underwater-Acoustic Target Recognition

Journal of Marine Science and Engineering
This paper proposes an underwater-acoustic class-incremental few-shot learning (UACIL) method for streaming data processing in practical underwater-acoustic target recognition scenarios. The core objective is to expand classification capabilities for new
Wenbo Wang, Ye Li, Tongsheng Shen, Dexin Zhao   +3 more
doaj   +3 more sources

Underwater acoustic target recognition using attention-based deep neural network [PDF]

JASA Express Letters, 2021
Underwater acoustic target recognition based on ship-radiated noise is difficult owing to the complex marine environment and the interference by multiple targets. As an important technology for target recognition, deep-learning has high accuracy but poor
Xu Xiao, Wenbo Wang, Qunyan Ren, Peter Gerstoft, Li Ma   +4 more
doaj   +4 more sources

An efficient transformer architecture with depthwise separable convolutions for high-accuracy underwater acoustic target recognition. [PDF]

Sci Rep
Underwater Acoustic Target Recognition (UATR) plays a vital role in maritime security and defense, requiring accurate and efficient classification of marine vessels based on their sonar acoustic emissions.
Mahmud NA, Zhang T, Iqbal Y, Sumona FB, Azaz I, Geng Y, Khan W, Kharma QM, Rubanenko O.   +8 more
europepmc   +2 more sources

Underwater Acoustic Target Recognition with a Residual Network and the Optimized Feature Extraction Method

Applied Sciences, 2021
Underwater Acoustic Target Recognition (UATR) remains one of the most challenging tasks in underwater signal processing due to the lack of labeled data acquisition, the impact of the time-space varying intrinsic characteristics, and the interference from
Feng Hong, Chengwei Liu, Lijuan Guo, Feng Chen, Haihong Feng   +4 more
doaj   +2 more sources

Unraveling Complex Data Diversity in Underwater Acoustic Target Recognition through Convolution-based Mixture of Experts [PDF]

Expert Systems With Applications
Underwater acoustic target recognition is a difficult task owing to the intricate nature of underwater acoustic signals. The complex underwater environments, unpredictable transmission channels, and dynamic motion states greatly impact the real-world ...
Yuan Xie, Jiawei Ren, Ji Xu
semanticscholar   +3 more sources

Path-Routing Convolution and Scalable Lightweight Networks for Robust Underwater Acoustic Target Recognition. [PDF]

Sensors (Basel)
Highlights What are the main findings? A novel PR-Conv mechanism is proposed to adaptively extract multi-scale ship acoustic features. The model achieves 98.58% classification accuracy while using 94% fewer parameters than conventional architectures ...
Zhao Y, Chen M, Lu Y, Cheng L, Chen C, Li Y, Alkayem NF.   +6 more
europepmc   +2 more sources

A Survey of Underwater Acoustic Target Recognition Methods Based on Machine Learning

Journal of Marine Science and Engineering, 2023
Underwater acoustic target recognition (UATR) technology has been implemented widely in the fields of marine biodiversity detection, marine search and rescue, and seabed mapping, providing an essential basis for human marine economic and military ...
Xinwei Luo, Lu Chen, Hanlu Zhou, Hongli Cao   +3 more
doaj   +2 more sources