activity
20182021
most citedWasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

271 citations · 1k across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2020★ 1 cited

Ensemble emotion recognizing with multiple modal physiological signals

Jing Zhang, Yong Zhang, Suhua Zhan +1

Physiological signals that provide the objective repression of human affective states are attracted increasing attention in the emotion recognition field. However, the single signa…

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★ 165 cited

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…

cs.LG2018★ 235 cited

A deep learning-based remaining useful life prediction approach for bearings

Cheng Cheng, Guijun Ma, Yong Zhang +4

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining usef…