Crossmark

DSA-YOLO: A lightweight framework for industrial defect detection based on YOLOv11 with two-stage cascaded knowledge distillation

Published Online: 2025-09-22

Published Print: 2025-11

Authors

Lian, Xiaofeng

Sun, Xiao

Liu, He

Tan, Li

Li, Jintao
Funding

Funding for this research was provided by:

Chongqing Natural Science Foundation (CSTB2024NSCQ-MSX0687, CSTB2024NSCQ-MSX0687, CSTB2024NSCQ-MSX0687, CSTB2024NSCQ-MSX0687, CSTB2024NSCQ-MSX0687)

National Natural Science Foundation of China (62472010, 62472010, 62472010, 62472010)
License Information

Text and Data Mining valid from 2025-09-22

Version of Record valid from 2025-09-22
More Information

Article History

Received: 4 June 2025

Revised: 19 July 2025

Accepted: 24 July 2025

First Online: 22 September 2025

Declarations

:

: The authors have no conflicts of interest to declare that are relevant to the content of this article.

: The authors declare no competing interests.

Document is current