Improved YOLOv3 Integrating SENet and Optimized GIoU Loss for Occluded Pedestrian Detection

Improved YOLOv3 Integrating SENet and Optimized GIoU Loss for Occluded Pedestrian Detection

Occluded pedestrian detection faces huge challenges. False positives and false negatives in crowd occlusion scenes will reduce the accuracy of occluded pedestrian detection. To overcome this problem, we proposed an improved you-only-look-once version 3 (YOLOv3) based on squeeze-and-excitation networ...

Full description

Bibliographic Details
Main Authors: Qiangbo Zhang, Yunxiang Liu, Yu Zhang, Ming Zong, Jianlin Zhu
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Sensors
Subjects:
occluded pedestrian detection
false positives
false negatives
loss function
Online Access:https://www.mdpi.com/1424-8220/23/22/9089

Similar Items

Similar Items