78 citations · 277 across the 11 of their papers we have counts for
12 papers
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…
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…
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.…
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…
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…
Underwater Acoustic Target Recognition based on Smoothness-inducing Regularization and Spectrogram-based Data Augmentation
Ji Xu, Yuan Xie, Wenchao Wang
Underwater acoustic target recognition is a challenging task owing to the intricate underwater environments and limited data availability. Insufficient data can hinder the ability…
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform
Yuan Xie, Jiawei Ren, Ji Xu
Analyzing the ocean acoustic environment is a tricky task. Background noise and variable channel transmission environment make it complicated to implement accurate ship-radiated no…
Learning Music Sequence Representation from Text Supervision
Tianyu Chen, Yuan Xie, Shuai Zhang +3
Music representation learning is notoriously difficult for its complex human-related concepts contained in the sequence of numerical signals. To excavate better MUsic SEquence Repr…
Underwater-Art: Expanding Information Perspectives With Text Templates For Underwater Acoustic Target Recognition
Yuan Xie, Jiawei Ren, Ji Xu
Underwater acoustic target recognition is an intractable task due to the complex acoustic source characteristics and sound propagation patterns. Limited by insufficient data and na…
Advancing underwater acoustic target recognition via adaptive data pruning and smoothness-inducing regularization
Yuan Xie, Tianyu Chen, Ji Xu
Underwater acoustic recognition for ship-radiated signals has high practical application value due to the ability to recognize non-line-of-sight targets. However, due to the diffic…
MoEC: Mixture of Expert Clusters
Yuan Xie, Shaohan Huang, Tianyu Chen +1
Sparsely Mixture of Experts (MoE) has received great interest due to its promising scaling capability with affordable computational overhead. MoE converts dense layers into sparse…
Task-Specific Expert Pruning for Sparse Mixture-of-Experts
Tianyu Chen, Shaohan Huang, Yuan Xie +5
The sparse Mixture-of-Experts (MoE) model is powerful for large-scale pre-training and has achieved promising results due to its model capacity. However, with trillions of paramete…