YOLOv10-Based Real-Time Pedestrian Detection for Autonomous Vehicles

Yan Li, Waiyie Leong, Hongli Zhang · 2024

Accurate pedestrian detection is increasingly important for safety as autonomous driving technology advances. This paper presents a real-time pedestrian detection method based on YOLOvlO. The technique creates an efficient real-time object detection model by enhancing the backbone network with EfficientNet and C2F-DM modules, integrating the BiFormer module in the neck network, and incorporating a multi-scale feature fusion detection head. Experimental results show that YOLOvlO can achieve efficient multi-scale pedestrian detection, even in complex backgrounds.

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