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相关概念视频

Fixation and Sectioning01:03

Fixation and Sectioning

Two basic types of preparation are used to visualize specimens with a light microscope: wet mounts and fixed specimens.
The simplest type of preparation is the wet mount, in which the specimen is placed in a drop of liquid on the slide. A liquid specimen can be directly deposited on the slide using a dropper. Solid specimens, such as skin scraping, can be placed on the slide before adding a drop of liquid to prepare the wet mount. Sometimes the liquid is simply water, but stains are often added...

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相关实验视频

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Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
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我们已经解决了眼球膜细分吗? 复习和评论 复习和评论

Andreas M Kist1, Michael D Llinger2

  • 1Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universit.±t Erlangen-N..rnberg (FAU), 91052 Erlangen, Germany.

Journal of voice : official journal of the Voice Foundation
|December 7, 2024
PubMed
概括

使用深度学习的自动化喉细分显示了对语音生理学研究的希望. 然而,仍然存在一些挑战,这表明科学界对完善语音折叠运动分析的持续兴趣.

关键词:
深度学习.. 喉细分.. 声.. 量化.. 喉区域.. 图像处理.. 图像分析.. 深度神经网络..

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Author Spotlight: Advancements in the Fabrication of Synthetic Vocal Fold Models for Phonetic and Robotic Applications
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科学领域:

  • 语音生理学和生物力学.
  • 医学图像分析和计算建模.

背景情况:

  • 量化语音生理学对于理解声功能至关重要.
  • 在过去的20年里,用于声运动分析的喉细分得到了人们的关注.
  • 完全自动化喉细分一直是一个持续的挑战.

研究的目的:

  • 突出眼球细分的持续挑战和机遇.
  • 为了强调喉细分的持续科学相关性.
  • 讨论自动语音折叠运动分析的未来.

主要方法:

  • 审查深度学习方法,以进行大脑垂体细分.
  • 分析自动化细分的当前局限性.
  • 讨论现场开放的研究问题.

主要成果:

  • 深度学习已经实现了近乎完全自动化的光环细分解决方案.
  • 尽管取得了进展,但完全自动化和稳健性仍在开发中.
  • 一些"开放的建筑工地"仍在喉细分研究中.

结论:

  • 喉细分仍然是语音研究的科学调查的一个重要领域.
  • 需要进一步的进步来完全自动化和验证细分技术.
  • 该领域需要继续进行研究,以加强声动态的量化.