Improved YOLOv8 Detection Algorithm in Security Inspection Image
This work addresses security inspection challenges for public safety applications, but it appears incremental as it builds on the existing YOLOv8 framework.
The paper tackled the problem of overlapping objects, false detection, and missed detection in X-ray security inspection images by proposing an improved YOLOv8-based algorithm, resulting in enhanced detection performance for contraband.
Security inspection is the first line of defense to ensure the safety of people's lives and property, and intelligent security inspection is an inevitable trend in the future development of the security inspection industry. Aiming at the problems of overlapping detection objects, false detection of contraband, and missed detection in the process of X-ray image detection, an improved X-ray contraband detection algorithm CSS-YOLO based on YOLOv8s is proposed.