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

Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

7.3K
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
7.3K

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 authorSame journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Holistic Invariant Retracing for Distortion-Resilient Multi-Modal Learning in Spatial Transcriptomics.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Demonstration of efficient predictive surrogates for large-scale quantum processors.

Nature communications·2026
Same author

A DeepSeek-powered AI system for automated chest radiograph interpretation in clinical practice.

Nature communications·2026
Same author

NoisePO: Efficient Semantic Noise Generation and Ranking for Diffusion-Based Text-to-Image Synthesis.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Stability and Generalization for Distributed SGDA.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
查看所有相关文章

相关实验视频

Updated: May 16, 2025

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

12.2K

从缺失的作品变成了杰作:用上下文适应的扩散来完成图像.

Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou

    IEEE transactions on pattern analysis and machine intelligence
    |April 4, 2025
    PubMed
    概括
    此摘要是机器生成的。

    通过使用上下文适应差异 (CAD) 模型对准已知和未知图像区域,ConFill提高了图像的完整性. 这种新的框架确保了无集成和在生成的内容中增强了细节,优于现有的方法.

    更多相关视频

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer
    07:54

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

    Published on: October 15, 2015

    8.0K
    Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
    10:33

    Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

    Published on: August 14, 2019

    8.4K

    相关实验视频

    Last Updated: May 16, 2025

    Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
    13:26

    Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

    Published on: August 11, 2016

    12.2K
    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer
    07:54

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

    Published on: October 15, 2015

    8.0K
    Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
    10:33

    Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

    Published on: August 14, 2019

    8.4K

    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 机器学习 机器学习

    背景情况:

    • 图像完成很困难,扩散模型努力将生成的内容与现有图像部分连贯地融合在一起.
    • 现有的方法缺乏明确的空间和语义对齐,导致不一致性和糟糕的整合.

    研究的目的:

    • 介绍ConFill,一个用于高保真图像完成的新框架.
    • 解决基于扩散的图像完成中的连贯性和整合性挑战.

    主要方法:

    • 开发了一个上下文适应差异 (CAD) 模型,以对齐已知和未知的图像区域的中间分布.
    • 实施了动态采样机制,以适应性地完善复杂地区的采样率.

    主要成果:

    • 在每个扩散步骤中,ConFill 逐渐减少生成和原始图像内容之间的差异.
    • 动态采样机制提高了恢复区域的细节性和整合性.
    • 广泛的实验表明ConFill超越了当前最先进的图像完成方法.

    结论:

    • ConFill通过实现与上下文一致且无集成的结果,为图像完成建立了新的基准.
    • 拟议的CAD模型和动态采样机制有效地解决了生成模型中的连贯性问题.