A consistency regularization based semi-supervised learning approach for intelligent fault diagnosis of rolling bearing
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2020.107987
Abstract: Abstract Deep learning has been widely used nowadays to achieve an automated fault diagnosis of rolling bearings. However, most of deep learning based bearing fault diagnosis methods are based on the assumption that the recorded… read more here.
Keywords: fault; fault diagnosis; consistency; consistency regularization ... See more keywords
Hybrid Semi-Supervised Learning for Rotating Machinery Fault Diagnosis Based on Grouped Pseudo Labeling and Consistency Regularization
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3269112
Abstract: Applying semi-supervised learning (SSL) methods, such as pseudo labeling and consistency regularization, to rotating machinery fault diagnosis alleviates the difficulty of obtaining a large amount of labeled data in industrial practice. The low accuracy of… read more here.
Keywords: consistency; consistency regularization; pseudo labeling; fault diagnosis ... See more keywords
Semisupervised Seizure Prediction in Scalp EEG Using Consistency Regularization
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Healthcare Engineering"
DOI: 10.1155/2022/1573076
Abstract: Early prediction of epilepsy seizures can warn the patients to take precautions and improve their lives significantly. In recent years, deep learning has become increasingly predominant in seizure prediction. However, existing deep learning-based approaches in… read more here.
Keywords: prediction; semisupervised seizure; consistency regularization; consistency ... See more keywords