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

Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

82
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
82

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

Multi-Physics Monotone Score Transport for Unsupervised Domain Adaptation of Continuous Tool Wear Prediction.

Sensors (Basel, Switzerland)·2026
Same author

Noise-robust reward machine induction via probabilistic modeling and genetic local search.

Scientific reports·2026
Same author

Astragaloside IV Exhibited Antidiabetic Effects by Improving Glucose Metabolism, Repairing Damaged Gut Barrier and Regulating Intestinal Microbiota.

Phytotherapy research : PTR·2026
Same author

Disease progression modeling of Alzheimer's disease based on variational probability principal component analysis.

PloS one·2026
Same author

Dual-function CRISPR/Cas12a assisted strand displacement reaction with RuHex-loaded DNA condensates for ultrasensitive electrochemical detection of hepatocellular carcinoma mRNA.

Biosensors & bioelectronics·2026
Same author

Machine Learning Accelerated Design of Self-Assembled Monolayers for High-Performance Perovskite Solar Cells.

The journal of physical chemistry letters·2026
Same journal

Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

IEEE transactions on visualization and computer graphics·2026
Same journal

ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
查看所有相关文章

相关实验视频

Updated: Jul 16, 2025

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
06:48

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

Published on: May 10, 2020

3.6K

超级UDF:自主监督的UDF对表面重建的估计.

Hui Tian, Chenyang Zhu, Yifei Shi

    IEEE transactions on visualization and computer graphics
    |September 22, 2023
    PubMed
    概括
    此摘要是机器生成的。

    超级UDF引入了使用未签名距离函数 (UDF) 进行表面重建的自我监督学习. 这种方法提高了效率和稳定性,即使用稀疏的数据,通过利用学习的几何先验和新的规范化技术来提高效率和稳定性.

    更多相关视频

    Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
    08:59

    Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

    Published on: October 28, 2018

    7.1K
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    9.9K

    相关实验视频

    Last Updated: Jul 16, 2025

    Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
    06:48

    Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

    Published on: May 10, 2020

    3.6K
    Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
    08:59

    Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

    Published on: October 28, 2018

    7.1K
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    9.9K

    科学领域:

    • 计算机视觉 计算机视觉
    • 计算机图形 计算机图形
    • 机器学习 机器学习

    背景情况:

    • 表面重建对于3D建模和分析至关重要.
    • 无符号距离函数 (UDF) 在表示开放表面方面具有优势.
    • 现有的基于学习的方法面临着稀少数据和效率的挑战.

    研究的目的:

    • 为基于UDF的表面重建开发一个自我监督的学习框架.
    • 提高UDF估计的效率和稳定性,特别是在稀疏采样场景中.
    • 引入一种新的网状取方法,从已学习的UDF中提取.

    主要方法:

    • 提出了SuperUDF,一种用于UDF估计的自我监督学习方法.
    • 结合了之前学习的几何学,以进行高效的训练.
    • 引入了一种新的规范化损失,用于对稀疏采样的稳定性.
    • 开发了一种基于学习的网格提取技术.

    主要成果:

    • 与最先进的方法相比,SuperUDF表现出卓越的性能.
    • 在重建质量和计算效率方面取得了改进.
    • 在多个公共数据集上验证,显示了对稀疏采样的稳定性.

    结论:

    • 超级UDF提供了一种有效和高效的解决方案,用于使用UDFs进行基于学习的表面重建.
    • 拟议的方法推进了处理稀疏数据的最先进技术,用于3D表面估计.
    • 未来的工作包括发布更广泛采用研究的代码.