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

Vision01:24

Vision

52.9K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
52.9K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

4.3K
Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
4.3K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

508
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
508

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

Development and validation of an interpretable model based on ultrasound radiomics for predicting Ki-67 expression levels in breast cancer.

Translational cancer research·2026
Same author

Seasonal shifts in mercury speciation and relative methylation potential in cold-arid seasonally ice-covered lakes.

Environmental pollution (Barking, Essex : 1987)·2026
Same author

Sex-Specific Adaptive Strategies of <i>Populus euphratica</i> Along Developmental and Canopy Gradients Based on Leaf Trait Networks.

Plants (Basel, Switzerland)·2026
Same author

Spatial Distribution, Risk Assessment, and Source Apportionment of Heavy Metals in Soils from the Sorghum Cultivation Base in the Chishui River Basin, China.

Toxics·2026
Same author

Global and Local Visual-Textual Alignment for Open Vocabulary Object Detection.

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

A machine-learning-based reconstruction of surface mass balance over the Greenland Ice Sheet from 1950 to 2020.

Scientific data·2026

相关实验视频

Updated: May 24, 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

低水平视觉中的扩散模型:一项调查

Chunming He, Yuqi Shen, Chengyu Fang

    IEEE transactions on pattern analysis and machine intelligence
    |March 3, 2025
    PubMed
    概括

    本文回顾了低水平视觉任务的无声扩散模型,并提供了对它们的理论,应用和未来方向的全面概述. 它综合了扩散模型的进步,用于高质量的图像生成和处理.

    科学领域:

    • 计算机视觉 计算机视觉
    • 深度学习 (Deep Learning) 是一种深度学习.
    • 生成型模型 生成型模型

    背景情况:

    • 深度生成模型在低水平视力方面表现出色.
    • 扩散模型对于高质量的图像生成具有突出地位.
    • 缺乏对低水平视觉中的扩散模型的全面调查.

    研究的目的:

    • 提供第一个综合性审查,在低水平视觉中消除噪声的扩散模型.
    • 为了涵盖理论和实践的贡献.
    • 综合进展并确定未来的研究方向.

    主要方法:

    • 概述了三个一般的扩散建模框架.
    • 探索与其他深度生成模型的连接.
    • 根据框架和应用进行分类的扩散模型.
    • 经过审查的基准和评估指标.
    • 在六个代表性任务中评估了扩散模型.

    主要成果:

    • 扩散模型在低水平视觉中显示出强大的生成能力.
    • 应用范围包括自然图像处理,医学成像,遥感和视频处理.
    • 广泛的评估显示了定量和质量的表现.

    更多相关视频

    Visualizing Visual Adaptation
    04:43

    Visualizing Visual Adaptation

    Published on: April 24, 2017

    8.9K
    From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
    15:10

    From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

    Published on: October 9, 2014

    11.4K

    相关实验视频

    Last Updated: May 24, 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
    Visualizing Visual Adaptation
    04:43

    Visualizing Visual Adaptation

    Published on: April 24, 2017

    8.9K
    From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
    15:10

    From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

    Published on: October 9, 2014

    11.4K

    结论:

    • 脱光扩散模型对于低水平视觉任务至关重要.
    • 目前存在的局限性,有前途的未来研究方向被确定.
    • 本次审查促进了对现场传播模型的更深入理解.