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使用人工智能获取体温和识别
Ana L Afonso1, Gil Lopes2, A Fernando Ribeiro3
1Mechanical Engineering Department, University of Minho, 4800-058 Guimarães, Portugal.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
这项研究引入了一种自动化系统,用于使用人工智能和双摄像头测量体温. 与手动技术相比,新方法提高了准确性,并减少了动物的压力.
科学领域:
- 动物生物学 动物生物学
- 计算机视觉 计算机视觉
- 热成像是一种热成像技术.
背景情况:
- 在实验室动物中手动测量体温是不准确的,可能会引起痛苦.
- 使用热摄像头的半手动方法耗时且不完全自动.
研究的目的:
- 为了在实验室环境中自动化的体温获取过程.
- 开发一种非侵入性和准确的方法来监测动物生理学.
主要方法:
- 使用双摄像头系统 (RGB和热) 进行同时数据捕获.
- 开发了一种人工智能模型 (YOLOv5),用于自动检测和定位体部位.
- 创建了一个定制的图像数据集,用于训练AI模型.
- 实现了坐标转换,用于从热图像到RGB图像的准确温度映射.
主要成果:
- 在使用YOLOv5.5检测及其身体部位时,获得了高精度 (90.00%) 和回忆力 (98.80%).
- 成功自动化了温度获取过程,克服了低对比度环境的挑战.
- 能够对的特定身体部位进行准确的温度读数.
结论:
- 开发的自动化系统显著提高了动物体温测量的准确性和效率.
- 这种由人工智能驱动的方法为生物研究的传统方法提供了一个不那么紧张和更可靠的替代方案.
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