Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Derivatives of Inverse Trigonometric Functions01:30

Derivatives of Inverse Trigonometric Functions

A ship tracking an approaching aircraft relies on geometric measurements to find out the aircraft’s position relative to the observer. By measuring the slant distance to the aircraft and the angle of elevation, the horizontal and vertical components of the distance can be obtained using trigonometric relationships. This geometric approach provides a basis for analyzing how the observed angle changes as the aircraft moves closer to the ship.To examine the mathematical behavior of the angle of...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Fe(II)-driven abiotic-biotic relay alleviates denitrification bottleneck via chemical nitrite reduction and intracellular carbon.

Water research·2026
Same author

The overlooked risk of horizontal transfer of plasmid-borne antibiotic resistance genes induced by organophosphate esters in aquaculture environments.

Water research·2026
Same author

Ecological plasticity of <i>Halanaerobium</i> microorganisms across terrestrial saline to hypersaline subsurface environments.

Microbiology spectrum·2026
Same author

Lipid nanoparticle composition directs systemic trafficking and tissue-specific T cell immunity after intramuscular injection.

Nature biomedical engineering·2026
Same author

Differential sulfur activity governs electroreductive decomplexation of Cu(II)-EDTA for simultaneous copper and ligand recovery.

Water research·2026
Same author

Construction and verification of 5-year survival prediction model for post-op ESCC patients.

Frontiers in oncology·2026

相关实验视频

Updated: May 10, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K

快速的灵敏度控制方法与可差分光学.

Zheng Ren, Wenguan Zhang, Tingting Jiang

    Optics express
    |August 13, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究提出了一种快速的方法来控制可微分光学中的镜头耐受性灵敏度. 它确保了稳定的光学系统性能,尽管制造变化,对于计算成像至关重要.

    更多相关视频

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
    09:43

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

    Published on: March 20, 2017

    10.0K
    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
    09:01

    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

    Published on: April 4, 2017

    8.7K

    相关实验视频

    Last Updated: May 10, 2026

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
    06:25

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

    Published on: February 12, 2014

    8.5K
    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
    09:43

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

    Published on: March 20, 2017

    10.0K
    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
    09:01

    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

    Published on: April 4, 2017

    8.7K

    科学领域:

    • 光学和光子学 在光学和光子学.
    • 计算成像技术的成像
    • 机器学习 机器学习

    背景情况:

    • 微分光学将光学设计与图像处理相结合,以实现关节优化.
    • 在优化过程中控制镜头容忍灵敏度是一个重大挑战,导致性能降低.
    • 现有的方法很难有效地管理对制造和装配公差的敏感性.

    研究的目的:

    • 为可微分光学提出一种快速灵敏度控制方法.
    • 为了解决耐受性敏感性,降解均性和边界对称性.
    • 为了实现光学系统和神经网络的强大的联合优化.

    主要方法:

    • 开发了一种针对各种光学模型量身定制的灵敏度控制方法.
    • 使用波线聚焦来提高优化稳定性,通过补偿失焦.
    • 利用光路差异方法通过避免重复的光线跟踪来降低计算成本.

    主要成果:

    • 在先进的广角和远距离智能手机镜头上成功验证了该方法.
    • 证明了对耐受性敏感性,均性和对称性的有效控制.
    • 与传统方法相比,实现了计算成本的显著降低.

    结论:

    • 拟议的方法为可微分光学中的脱敏化优化提供了一个实际的解决方案.
    • 实现光学系统和神经网络的更可靠的联合设计,用于计算成像.
    • 在先进的成像应用中为光学无敏化开辟了新的途径.