Multi-scale attentional feature fusion-based traffic sign detection using image dehazing process of SPP-CAE and improved optimization of YOLOv9 model
Thiyagarajan V, Vidhyapathi CM · 2026
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Description
Thiyagarajan V and Vidhyapathi CM build a system to spot road signs in poor weather, in a 2026 paper. Self driving cars need to read signs fast and well, yet fog, glare, and blocks in view can foil them. The authors add a cleaning step that clears haze from images before detection.
Cleaned images pass to a detection network built on a recent YOLO model, tuned by a new search method. The network blends features at several scales and weighs the most telling ones. On two large road data sets the system scored in the high ninety percent range for accuracy. Such gains could help driver aid tools in bad weather.
Catalog record
| CREATOR | Thiyagarajan V, Vidhyapathi CM |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 107 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |