JDGAN: Enhancing generator on extremely limited data via joint distribution
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.12.001
Abstract: Abstract Generative Adversarial Network (GAN) is a thriving generative model and considerable efforts have been made to enhance the generation capabilities via designing a different adversarial framework of GAN (e.g., the discriminator and the generator)… read more here.
Keywords: generator; joint distribution; extremely limited; jdgan enhancing ... See more keywords
Improved Generative Adversarial Network for Rotating Component Fault Diagnosis in Scenarios With Extremely Limited Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2021.3127636
Abstract: Traditional data-driven intelligent fault diagnosis methods for rotating component commonly assume that sufficient labeled data is available. However, the rotary machine works in a normal state most of the time in practical engineering, resulting in… read more here.
Keywords: diagnosis scenarios; rotating component; fault diagnosis; diagnosis ... See more keywords