ETSR-YOLO: An improved multi-scale traffic sign detection algorithm based on YOLOv5.

ABSTRACT: In the application of driverless technology, current traffic sign recognition methods are susceptible to the influence of ambient light interference, target size changes and complex backgrounds, resulting in reduced recognition accuracy. To address these challenges, this study introduces an optimisation algorithm called ETSR-YOLO, which is based on the YOLOv5s algorithm. First, this study improves the path aggregation network (PANet) of YOLOv5s to enhance multi-scale feature fusion by generating an additional high-resolution feature layer to improve the recognition of YOLOv5s for small-sized objects. Second, the study introduces two improved C3 modules that aim to suppress background noise interference and enhance the feature extraction capabilities of the network. Finally, the study uses

SUBMITTER: Liu H 

PROVIDER: S-EPMC10721062 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature