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
Dual Dynamic Consistency Regularization for Semi-Supervised Domain Adaptation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3374105
Abstract: The Vision Transformer (ViT) model serves as a powerful model to capture and comprehend global information, particularly when trained on extensive datasets. Conversely, the Convolutional Neural Network (CNN) model is beneficial to training with small… read more here.
Keywords: consistency regularization; model; cnn model; vit model ... 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
Conditional Consistency Regularization for Semi-Supervised Multi-Label Image Classification
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2023.3324132
Abstract: Consistency regularization has achieved great successes in Semi-Supervised Single-Label Image Classification (SS-SLC) with deep learning models, while few effort has been devoted to Semi-Supervised Multi-Label Image Classification (SS-MLC) with deep learning models. One intuitive solution… read more here.
Keywords: image; consistency regularization; image classification; label ... See more keywords
Instance Consistency Regularization for Semi-Supervised 3D Instance Segmentation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2024.3424243
Abstract: Large-scale datasets with point-wise semantic and instance labels are crucial to 3D instance segmentation but also expensive. To leverage unlabeled data, previous semi-supervised 3D instance segmentation approaches have explored self-training frameworks, which rely on high-quality… read more here.
Keywords: instance segmentation; instance; segmentation; consistency regularization ... 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
Refined Semi-Supervised Modulation Classification: Integrating Consistency Regularization and Pseudo-Labeling Techniques
Sign Up to like & getrecommendations! Published in 2024 at "Future Internet"
DOI: 10.3390/fi16020038
Abstract: Automatic modulation classification (AMC) plays a crucial role in wireless communication by identifying the modulation scheme of received signals, bridging signal reception and demodulation. Its main challenge lies in performing accurate signal processing without prior… read more here.
Keywords: regularization pseudo; consistency regularization; pseudo labeling; semi supervised ... See more keywords