FSH-DETR:基于可变形检测变压器 (DETR) 的高效端到端火灾,烟雾和人体检测
Tianyu Liang1, Guigen Zeng2,3
1School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
这项研究介绍了FSH-DETR,这是一个先进的物体检测系统,用于识别火灾,烟雾和人类. 它提高了关键安全应用的准确性和速度.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 火灾构成了严重的安全风险,造成伤亡和损失.
- 目前的物体检测方法难以检测小火灾/烟雾,而且计算成本昂贵.
研究的目的:
- 开发一个高效的端到端的物体探测器用于火灾,烟雾和人类检测.
- 为了解决检测小规模火灾和烟雾特征的局限性,并降低计算成本.
主要方法:
- 建议FSH-DETR,一个基于可变形DETR (检测转换器) 的物体探测器.
- 推出了一种新的混合编码器,集成SSFI (单独的单级特征交互模块) 和CCFM (基于CNN的跨度特征融合模块) 来实现多级特征融合.
- 集成PIoUv2 (联盟强大的十字路口) 界限框损失,以提高收速度和检测精度.
主要成果:
- 与最先进的方法相比,FSH-DETR显示出更高的性能.
- 在公开数据集上实现了66.7%的平均平均精度 (mAP) 和84.2%的mAP50.
结论:
- 拟议的FSH-DETR有效地检测火灾,烟雾和人类,并提高了准确性和效率.
- 新的混合编码器和PIoUv2损失函数有助于增强多尺度特征处理和更快的融合.
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