Skip to main navigation
Skip to search
Skip to main content
Aston Research Explorer Home
Help & FAQ
Home
Research units
Profiles
Research Outputs
Datasets
Student theses
Activities
Press/Media
Prizes
Equipment
Search by expertise, name or affiliation
Transfer-Learning-for-Fault-Diagnosis
Ming Zhang
Mechanical, Biomedical & Design Engineering
Research output
:
Non-textual form
›
Software
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Transfer-Learning-for-Fault-Diagnosis'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Adversarial Learning
50%
Bearing Fault Diagnosis
100%
Deep Transfer Models
50%
Domain Adaptation
50%
Domain Adaptive
50%
Fault Diagnosis
100%
Gear Fault Diagnosis
50%
Learning Adaptive
50%
Multi-adversarial Networks
50%
Multistage Centrifugal Pump
50%
Transfer Domain
50%
Transfer Learning
100%
Variational Mode Decomposition
50%
Wasserstein Distance
50%
Engineering
Centrifugal Pump
20%
Fault Diagnosis
100%
Gearbox
20%
Multistage
20%
Rolling Bearings
20%
Transfer Learning
100%
Variational Mode Decomposition
20%
Medicine and Dentistry
Fault Diagnosis
100%
Transfer of Learning
100%
Biochemistry, Genetics and Molecular Biology
Transfer of Learning
100%