Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject learning with noisy labels (LNL)
Showing results 1 to 2 of 2
| Issue Date | Title | Author(s) |
|---|---|---|
| 13-Nov-2025 | Label-Noise-Resistant Time-Series Classification With Self-Supervised Label Correction | He, Y; Wang, Z; Liu, W; Fang, J; Chen, L; Song, Z |
| 22-Oct-2025 | Learning With Noisy Labels for Industrial Time Series Outlier Detection: A Transformer-Embedded Contrastive Learning Framework | Fang, J; Wang, Z; Liu, W; Zeng, N; He, Y; Cao, Y; Chen, L; Liu, X |