YOLOv8n-GCB： Lightweight Fire Detection Network

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Graphic and Image Processing | 更新时间：2025-06-24

- YOLOv8n-GCB： Lightweight Fire Detection Network
- “In the field of object detection, the YOLOv8n GCB algorithm has improved the accuracy of fireworks recognition, with an average recognition rate increase of 6.1% and a detection speed of 33.4 FBS, achieving real-time detection.”
- Software Guide Vol. 24, Issue 6, Pages: 185-191(2025)
- 作者机构：
  
  1.武汉纺织大学，计算机与人工智能学院
  2.湖北省服装信息化工程技术研究中心
  3.纺织服装智能化湖北省工程研究中心，湖北武汉 430200
- 作者简介：
- 基金信息：
- DOI：10.11907/rjdk.241396
  CLC： TP391.4
- Received：22 April 2024，
  
  Published：16 June 2025
- 稿件说明：
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韩逸,李敏.YOLOv8n-GCB：轻量化的烟火检测网络[J].软件导刊,2025,24(06):185-191.

HAN Yi,LI Min.YOLOv8n-GCB： Lightweight Fire Detection Network[J].Software Guide,2025,24(06):185-191.
韩逸,李敏.YOLOv8n-GCB：轻量化的烟火检测网络[J].软件导刊,2025,24(06):185-191. DOI： 10.11907/rjdk.241396.

HAN Yi,LI Min.YOLOv8n-GCB： Lightweight Fire Detection Network[J].Software Guide,2025,24(06):185-191. DOI： 10.11907/rjdk.241396.

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