MFF’s overall structure.

<div><p>This study proposes an improved YOLOv8 model for vehicle and pedestrian detection in urban traffic monitoring systems. In order to improve the detection performance of the model, we introduced a multi-scale feature fusion module and an improved non-maximum suppression (NMS) algor...

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Bibliographic Details
Main Author:	Huili Dou (20896665) (author)
Other Authors:	Sirui Chen (192925) (author), Fangyuan Xu (1600204) (author), Yuanyuan Liu (136992) (author), Hongyang Zhao (1901329) (author)
Published:	2025
Subjects:	Sociology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified combining feature maps experimental results show model &# 8217 baseline yolov8 model mean average precision pedestrian detection effects improved yolov8 model yolov8 model pedestrian detection results prove improved non missed detection detection performance detection ability xlink "> visdrone2019 dataset study proposes screening process multiple categories maximum suppression map ). key indicators f1 score different sizes different scales candidate boxes algorithm based accurately identify
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MFF’s overall structure.

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