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Updated: Jun 22, 2025

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机器学习启发的纳米线分类方法基于纳米线阵列扫描电子显微镜图像

Enrico Brugnolotto1,2, Preslav Aleksandrov1, Marilyne Sousa2

  • 1James Watt School of Engineering, University of Glasgow, Glasgow, Scotland, UK.

Open research Europe
|July 3, 2024
PubMed
概括

本研究介绍了一种使用机器学习的新方法,用于在扫描电子显微镜图像中准确识别纳米线. 该技术实现了高精度和回忆,显示了研究和工业应用的潜力.

关键词:
计算机视觉 计算机视觉图像细分 图像细分机器学习是机器学习.显微镜成像成像技术纳米电线的纳米线.纳米材料是一种纳米材料.扫描电子显微镜扫描电子显微镜

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相关概念视频

Scanning Electron Microscopy01:07

Scanning Electron Microscopy

A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
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