Results 211 to 220 of about 4,866,384 (247)

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 ...
Ji Xu, Yuan Xie, Jiawei Ren
exaly   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

Underwater acoustic targets recognition algorithm based on NMF

2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2020
To 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, Zhichao Shan, Xianzhong Liu, Liang Yu   +3 more
openaire   +1 more source

Intelligent Recognition of Underwater Acoustic Target Noise on Underwater Glider Platform

2018 Chinese Automation Congress (CAC), 2018
The underwater acoustic target detection system based on the underwater glider platform requires the platform itself to have the ability of target automatic tracking, identification and evaluation, but the traditional methods of underwater target noise identification have strong human-computer interaction characteristics.
Zhang Shao-Kang, Tian De-Yan, Wang Chao, Zhang Xiao-Chuan   +3 more
openaire   +1 more source

An Effective Convolutional and Transformer Cooperation Network for Underwater Acoustic Target Recognition

Engineering Applications of Artificial Intelligence
Xiangyang Zeng, Anqi Jin
exaly   +3 more sources

Underwater Acoustic Target Recognition Based on ReLU Gated Recurrent Unit

2020 6th International Conference on Robotics and Artificial Intelligence, 2020
In general, the traditional acoustic models'(e. g. Gaussian mixture model, GMM) for underwater acoustic target recognition (UATR) performance in sequential data has so far been disappointing. In contrast, Recurrent Neural Network (RNN) is a powerful tool for sequential data.
Xiaodong Sun, Xiaohan Yin, Yaguang Yin, Peishun Liu, Liang Wang 0033, Ruichun Tang   +5 more
openaire   +2 more sources

An Underwater Acoustic Target Recognition Method Based on Transfer Learning

2024 9th International Conference on Electronic Technology and Information Science (ICETIS)
 Underwater acoustic target recognition(UATR)is a challenging task Due to the high cost of sampling data, it is difficult to build a large-scale dataset.In this study,a new method based on transfer learning with a VGG16 model(Transfer-VGG16) is developed in which three-dimensional(3-D)data is used as the input.Use the dataset obtained in real scenarios
Xiaozhuo Yang, Huapeng Yu, Hanmin Sheng, Wenlong Zeng, Qingyuan He, Junyang Tu   +5 more
openaire   +1 more source

CA_MobileNetV2 for Underwater Acoustic Target Recognition

2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2023
Gao Tian, Haiyang Yao, Wang Haiyan, Wu Fan, Chen Xiao   +4 more
openaire   +2 more sources

An Underwater Acoustic Target Recognition Method Based on AMNet

IEEE Geoscience and Remote Sensing Letters, 2023
Biao Wang 0002, Wei Zhang 0317, Yunan Zhu 0004, Chengxi Wu, Shizhen Zhang   +4 more
openaire   +1 more source

Intelligent Recognition of Underwater Acoustic Target Noise by Multi-Feature Fusion

2018 11th International Symposium on Computational Intelligence and Design (ISCID), 2018
The traditional methods of underwater acoustic target recognition need to manually extract the feature data, and the recognition process has strong human-computer interaction characteristics, which couldn't meet the demand of intelligence of underwater acoustic target recognition in the future.
Shaokang Zhang, Shihong Xing
openaire   +2 more sources

Underwater Acoustic Target Recognition with Fusion Feature

2021
Pengyuan Qi, Jianguo Sun, Yunfei Long, Liguo Zhang, Tianye   +4 more
openaire   +1 more source