Results 11 to 20 of about 41,227 (280)
Underwater target recognition methods based on the framework of deep learning: A survey
International Journal of Advanced Robotic Systems, 2020 The accuracy of underwater target recognition by autonomous underwater vehicle (AUV) is a powerful guarantee for underwater detection, rescue, and security.
Bowen Teng, Hongjian Zhao
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Artificial Intelligence-Based Underwater Acoustic Target Recognition: A Survey
Remote SensingUnderwater acoustic target recognition has always played a pivotal role in ocean remote sensing. By analyzing and processing ship-radiated signals, it is possible to determine the type and nature of a target.
Sheng Feng +3 more
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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 +4 more
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Joint learning model for underwater acoustic target recognition
Knowledge-Based Systems, 2023 Sheng-Zhao Tian +3 more
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Sonar image recognition of underwater target based on convolutional neural network
Xibei Gongye Daxue Xuebao, 2021 Underwater target recognition is one core technology of underwater unmanned detection. To improve the accuracy of underwater automatic target recognition, a sonar image recognition method based on convolutional neural network was proposed and the ...
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Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks [PDF]
, 2020 © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hopkinson, B. M., King, A. C., Owen, D. P., Johnson-Roberson, M., Long, M. H., & Bhandarkar, S.
Bhandarkar, Suchendra M. +5 more
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The Journal of the Acoustical Society of America, 2022 Underwater acoustic target recognition is an intractable task due to the complex acoustic source characteristics and sound propagation patterns. Limited by insufficient data and narrow information perspective, recognition models based on deep learning seem far from satisfactory in practical underwater scenarios. Although underwater acoustic signals are
Xie, Yuan, Ren, Jiawei, Xu, Ji
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Underwater Acoustic Target Recognition Based on Attention Residual Network
Entropy, 2022 Underwater acoustic target recognition is very complex due to the lack of labeled data sets, the complexity of the marine environment, and the interference of background noise. In order to enhance it, we propose an attention-based residual network recognition method (AResnet).
Juan Li +4 more
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Few-shot learning for joint model in underwater acoustic target recognition
Scientific Reports, 2023 In underwater acoustic target recognition, there is a lack of massive high-quality labeled samples to train robust deep neural networks, and it is difficult to collect and annotate a large amount of base class data in advance unlike the image recognition
Shengzhao Tian +4 more
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Underwater acoustic target recognition method based on a joint neural network.
PLoS ONE, 2022 To improve the recognition accuracy of underwater acoustic targets by artificial neural network, this study presents a new recognition method that integrates a one-dimensional convolutional neural network and a long short-term memory network.
Xing Cheng Han +3 more
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