Deep semi-supervised regression via pseudo-label filtering and calibration
-
Published:2024-08
Issue:
Volume:161
Page:111670
-
ISSN:1568-4946
-
Container-title:Applied Soft Computing
-
language:en
-
Short-container-title:Applied Soft Computing
Author:
Jo YongwonORCID,
Kahng HyunguORCID,
Kim Seoung Bum
Reference35 articles.
1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges;Abdar;Inf. Fusion,2021
2. Natural language processing;Chowdhary,2020
3. Deep learning for motor imagery EEG-based classification: A review;Al-Saegh;Biomed. Signal Process. Control,2021
4. I. Misra, L.v.d. Maaten, Self-supervised learning of pretext-invariant representations, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 6707–6717.
5. W. Zhang, L. Zhu, J. Hallinan, S. Zhang, A. Makmur, Q. Cai, B.C. Ooi, Boostmis: Boosting medical image semi-supervised learning with adaptive pseudo labeling and informative active annotation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 20666–20676.