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 Author Song, Baoye
Showing results 1 to 2 of 2
| Issue Date | Title | Author(s) |
|---|---|---|
| 7-Aug-2026 | Data-centric deep learning for defect detection in fiber composite materials: A review of algorithms, challenges, and emerging trends | Han, Juntao; Wang, Zidong; Liu, Weibo; Song, Baoye; Wang, Chuang; Liu, Xiaohui |
| 15-Sep-2026 | YOLO-TDH: An object detection framework for power transmission line inspection | Song, Baoye; Zhao, Shihao; Liu, Weibo; Xue, Yani |