Analysis of Improved Logo Detection Performance of YOLOv11 in Autonomous Driving Environment
With the rapid development of autonomous driving technology, traffic sign detection, as a core component of environmental perception systems, faces challenges such as small target missed detection, complex background interference, and real-time requirements. Based on YOLOv11 model, this paper proposes an optimization scheme for traffic sign detection in the automatic driving scene, which effectively improves the detection accuracy of small targets and provides a new solution for the sign detection of the auto drive system.
Authors
- Jianfei Jiang (ORCID: https://orcid.org/0000-0002-5521-6197)
Institutions
- Queensland University of Technology (AU)
Publication Details
- Journal
- Applied and Computational Engineering
- Published
- 2025-08-13
- DOI
- https://doi.org/10.54254/2755-2721/2025.25898
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00