most citedUnraveling Complex Data Diversity in Underwater Acoustic Target Recognition through Convolution-based Mixture of Experts

51 citations · 95 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD2024★ 17 cited

Adversarial multi-task underwater acoustic target recognition: towards robustness against various influential factors

Yuan Xie, Ji Xu, Jiawei Ren +1

Underwater acoustic target recognition based on passive sonar faces numerous challenges in practical maritime applications. One of the main challenges lies in the susceptibility of…

cs.SD2024★ 15 cited

Advancing Robust Underwater Acoustic Target Recognition through Multi-task Learning and Multi-Gate Mixture-of-Experts

Yuan Xie, Jiawei Ren, Junfeng Li +1

Underwater acoustic target recognition has emerged as a prominent research area within the field of underwater acoustics. However, the current availability of authentic underwater…

cs.SD2024

DEMONet: Underwater Acoustic Target Recognition based on Multi-Expert Network and Cross-Temporal Variational Autoencoder

Yuan Xie, Xiaowei Zhang, Jiawei Ren +1

Building a robust underwater acoustic recognition system in real-world scenarios is challenging due to the complex underwater environment and the dynamic motion states of targets.…

cs.SD2024★ 12 cited

Guiding the underwater acoustic target recognition with interpretable contrastive learning

Yuan Xie, Jiawei Ren, Ji Xu

Recognizing underwater targets from acoustic signals is a challenging task owing to the intricate ocean environments and variable underwater channels. While deep learning-based sys…

cs.SD2024★ 51 cited

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

Yuan Xie, Jiawei Ren, Ji Xu

Underwater acoustic target recognition is a difficult task owing to the intricate nature of underwater acoustic signals. The complex underwater environments, unpredictable transmis…