Detection results of the improved YOLOv8s at low light intersections.

<p>Detection results of the improved YOLOv8s at low light intersections.</p>

Saved in:

Bibliographic Details
Main Author:	Xinwei Wang (352488) (author)
Other Authors:	Yue Hu (201714) (author), Qing Liang (654718) (author), Yujie He (3068052) (author), Li Zhou (54356) (author)
Published:	2025
Subjects:	Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified weight file size uav autonomous perception shown explosive growth insufficient feature capture injecting new vitality extract critical features enrich feature fusion efficient feature extraction enabling convolution operations 9 %, 4 sppf module incorporates scale feature processing mechanism captures long mean average precision improve detection accuracy algorithm introduces akconv model &# 8217 large convolution kernels improved algorithm achieves 33 %, respectively low altitude economy convolution kernels altitude economy detection precision original algorithm scale searches paper achieves lska mechanism improved yolov8s c2f module akconv allows accurate large detection recall 5 %, xlink "> thereby achieving study focuses security risks sampling shapes range dependencies precisely adapt perform rapid parameter count orderly operation model lightweighting low efficiency low airspace key support experimental results economic development
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items