Results 1 to 10 of about 20,770 (204)

Underwater Acoustic Target Recognition Based on Depthwise Separable Convolution Neural Networks [PDF]

Sensors, 2021
Facing the complex marine environment, it is extremely challenging to conduct underwater acoustic target feature extraction and recognition using ship-radiated noise.
Gang Hu, Kejun Wang, Liangliang Liu
doaj   +7 more sources

Underwater Acoustic Target Recognition Based on Attention Residual Network [PDF]

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.
Juan Li, Baoxiang Wang, Xuerong Cui, Shibao Li, Jianhang Liu   +4 more
doaj   +4 more sources

Deep convolution stack for waveform in underwater acoustic target recognition [PDF]

Scientific Reports, 2021
In underwater acoustic target recognition, deep learning methods have been proved to be effective on recognizing original signal waveform. Previous methods often utilize large convolutional kernels to extract features at the beginning of neural networks.
Shengzhao Tian, Duanbing Chen, Hang Wang, Jingfa Liu   +3 more
doaj   +5 more sources

Underwater acoustic target recognition method based on a joint neural network. [PDF]

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, Chenxi Ren, Liming Wang, Yunjiao Bai   +3 more
doaj   +4 more sources

Few-shot learning for joint model in underwater acoustic target recognition [PDF]

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, Di Bai, Junlin Zhou, Yan Fu, Duanbing Chen   +4 more
doaj   +4 more sources

Feature Extraction Methods for Underwater Acoustic Target Recognition of Divers [PDF]

Sensors
The extraction of typical features of underwater target signals and excellent recognition algorithms are the keys to achieving underwater acoustic target recognition of divers.
Yuchen Sun, Weiyi Chen, Changgeng Shuai, Zhiqiang Zhang, Pingbo Wang, Guo Cheng, Wenjing Yu   +6 more
doaj   +4 more sources

A Novel Underwater Acoustic Target Recognition Method Based on MFCC and RACNN [PDF]

Sensors
In ocean remote sensing missions, recognizing an underwater acoustic target is a crucial technology for conducting marine biological surveys, ocean explorations, and other scientific activities that take place in water.
Dali Liu, Hongyuan Yang, Weimin Hou, Baozhu Wang   +3 more
doaj   +3 more sources

Artificial Intelligence-Based Underwater Acoustic Target Recognition: A Survey

Remote Sensing
Underwater 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, Shuqing Ma, Xiaoqian Zhu, Ming Yan   +3 more
doaj   +3 more sources

An Underwater Acoustic Target Recognition Method Based on Restricted Boltzmann Machine [PDF]

Sensors, 2020
This article focuses on an underwater acoustic target recognition method based on target radiated noise. The difficulty of underwater acoustic target recognition is mainly the extraction of effective classification features and pattern classification ...
Xinwei Luo, Yulin Feng
doaj   +5 more sources

Underwater Acoustic Target Recognition Based on Supervised Feature-Separation Algorithm [PDF]

Sensors, 2018
For the purpose of improving the accuracy of underwater acoustic target recognition with only a small number of labeled data, we proposed a novel recognition method, including 4 steps: pre-processing, pre-training, fine-tuning and recognition.
Xiaoquan Ke, Fei Yuan, En Cheng
doaj   +5 more sources