# Improved YOLOv8 Detection Algorithm in Security Inspection Image

arXiv: https://arxiv.org/abs/2308.06452 · HTML: https://mlsanity.com/paper/2308.06452/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 21 references that are in the map.
- First posted on arXiv 12 Aug 2023.

## Builds on (most cited first, 10 of 10)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [Deformable DETR: Deformable Transformers for End-to-End Object Detection](https://mlsanity.com/paper/2010.04159/) (2020)
- [SSD: Single Shot MultiBox Detector](https://mlsanity.com/paper/1512.02325/) (2015)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [Soft-NMS -- Improving Object Detection With One Line of Code](https://mlsanity.com/paper/1704.04503/) (2017)
- [CSPNet: A New Backbone that can Enhance Learning Capability of CNN](https://mlsanity.com/paper/1911.11929/) (2019)
- [SIXray : A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images](https://mlsanity.com/paper/1901.00303/) (2019)
- [Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module](https://mlsanity.com/paper/2004.08656/) (2020)

## Built on by (most cited first, 2 of 2)

- [BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection](https://mlsanity.com/paper/2309.12585/) (2023)
- [Improving Generalization Performance of YOLOv8 for Camera Trap Object Detection](https://mlsanity.com/paper/2412.14211/) (2024)

## Abstract (arXiv)

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.