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相关概念视频

Microcracking in Concrete01:20

Microcracking in Concrete

110
Microcracking in concrete refers to the tiny cracks that can form within the material even before any external load is applied. These microcracks typically occur at the interface between the coarse aggregate and the hydrated cement paste, often as a result of differential volume changes prompted by variations in stress-strain behavior, as well as thermal and moisture movement. Initially, these microcracks remain stable and do not grow substantially until the concrete is stressed to about 30...
110

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相关实验视频

Updated: Jun 12, 2025

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
00:05

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在光学图像中检测牙裂的轻量级检测算法.

Zewen Xie1, Xian Hu2, Lide Guo3

  • 1School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China; School of Physics and Material Science, Guangzhou University, Guangzhou, 510006, China.

Computers in biology and medicine
|September 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种改进的物体检测算法,用于识别破裂的牙,显著减少模型大小,以方便部署. 优化的模型帮助牙医检测微妙的牙裂,改善早期诊断.

关键词:
破裂的牙检测检测器轻量级的算法 轻量级的算法对象检测检测对象检测对象检测光学图像图像 光学图像图像这就是YOLOv8的意义.

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Detection and Removal of Tooth-Colored Composite Resin Using the Fluorescence-Aided Identification Technique
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相关实验视频

Last Updated: Jun 12, 2025

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科学领域:

  • 牙科诊断 牙科诊断 牙科诊断
  • 计算机视觉 计算机视觉 计算机视觉
  • 人工智能的人工智能是人工智能.

背景情况:

  • 裂牙综合征 (CTS) 是导致牙脱落的常见原因,通常会出现微妙的早期症状.
  • 准确和早期发现牙裂对于有效治疗和预防牙脱落至关重要.

研究的目的:

  • 研究一种改进的物体检测算法,用于自动检测牙科光学图像中的裂.
  • 开发一个轻量级和可部署的模型用于临床使用.

主要方法:

  • 使用了3000多张牙科图像的数据集,包括真实临床图像.
  • 通过模型修剪和骨干更换等技术,YOLOv8对象检测模型得到了改进.
  • 分析了图像增强和注意力模块对模型性能的影响.

主要成果:

  • 模型修剪使参数减少了16.8%,GFLOPs减少了24.3%,性能影响最小.
  • 替换骨干网络的效果不如针对这个特定任务进行修剪那么高.
  • 图像增强和注意力模块对牙裂检测的YOLOv8性能影响最小.

结论:

  • 开发了一种改进的轻量级物体检测算法,用于检测牙裂.
  • 优化的模型适合在嵌入式设备上部署,协助牙科专业人员.
  • 这项技术有可能提高牙表面裂的早期识别.