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相关概念视频

Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

17.6K
The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
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Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

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Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
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Atomic Force Microscopy01:08

Atomic Force Microscopy

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Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...
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相关实验视频

Updated: Mar 16, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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J3SPM AI:一个集成的开源平台,用于人工智能辅助的图像分析和扫描探针显微镜中的图像引导工作流程.

SangHeon Lee1

  • 1School of Electronic-Mechanical Engineering, Robotics Engineering Major, Gyeongkuk National University, Gyungdongro 1375, Andong, Gyeongbuk 36729, Republic of Korea.

Micron (Oxford, England : 1993)
|March 14, 2026
PubMed
概括

J3SPM人工智能 (AI) 通过将AI工具集成到一个用户友好的平台,简化了扫描探针显微镜 (SPM) 分析. 这提高了图像质量和纳米级材料表征的吞吐量.

科学领域:

  • 材料科学 材料科学 材料科学
  • 纳米技术 纳米技术
  • 数据科学数据科学数据科学

背景情况:

  • 扫描探针显微镜 (SPM),特别是原子力显微镜 (AFM),对于纳米级材料的表征至关重要.
  • 现有的SPM方法面临图像质量和吞吐量方面的挑战,限制了实际应用.
  • 自动化方面的进步还没有完全解决这些持续存在的问题.

研究的目的:

  • 开发一个可访问的平台,将人工智能 (AI) 集成到 SPM 工作流中.
  • 克服在SPM分析中的图像质量和吞吐量方面的局限性.
  • 在SPM实验中实现人工智能辅助决策.

主要方法:

  • 开发J3SPM AI,一个开源的图形用户界面 (GUI) 平台.
  • 整合人工智能工具用于图像预处理,数据集构建,模型训练和推理.
  • 实施人工智能用于对象检测和兴趣区域识别,以指导数据采集.

主要成果:

  • J3SPM AI为人工智能辅助的SPM分析提供了一个统一的环境,消除了用户构建机器学习管道的需求.
  • 该平台支持基于图像的对象检测和区域识别,用于有针对性的重新扫描和数据采集.
  • 成功降低了将AI纳入SPM的技术障碍.
关键词:
原子力显微镜的原子力显微镜.深度学习是一种深度学习.高速原子力显微镜的高速原子力显微镜.这是开源的,是开源的.扫描探针显微镜扫描探针显微镜

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Last Updated: Mar 16, 2026

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结论:

  • J3SPM AI提供了一个实用的框架,可以通过人工智能驱动的见解来增强SPM实验.
  • 该平台促进了人工智能辅助的决策,提高了纳米分析中的效率和数据质量.
  • 授权研究人员在没有广泛的机器学习专业知识的情况下,利用人工智能用于先进的SPM应用程序.