activity
20192024
most citedWasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

271 citations · 620 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024

PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning

Xiaoyu Liu, Beitong Zhou, Zuogong Yue +1

Recently, the usage of Contrastive Representation Learning (CRL) as a pre-training technique improves the performance of learning with noisy labels (LNL) methods. However, instead…

eess.SP2021★ 158 cited

A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method

Sen Zhao, Yong Zhang, Shang Wang +2

Data-driven methods for remaining useful life (RUL) prediction normally learn features from a fixed window size of a priori of degradation, which may lead to less accurate predicti…

cs.LG2019★ 191 cited

A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series

Wenqian Jiang, Cheng Cheng, Beitong Zhou +2

This paper proposes a novel fault diagnosis approach based on generative adversarial networks (GAN) for imbalanced industrial time series where normal samples are much larger than…

cs.LG2019★ 271 cited

Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

Cheng Cheng, Beitong Zhou, Guijun Ma +2

The demand of artificial intelligent adoption for condition-based maintenance strategy is astonishingly increased over the past few years. Intelligent fault diagnosis is one critic…

cs.LG2019

A General End-to-end Diagnosis Framework for Manufacturing Systems

Ye Yuan, Guijun Ma, Cheng Cheng +4

The manufacturing sector is envisioned to be heavily influenced by artificial intelligence-based technologies with the extraordinary increases in computational power and data volum…