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

Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...

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

Re: Health-related quality of life in patients with newly diagnosed advanced ovarian cancer receiving maintenance olaparib plus bevacizumab (PAOLA-1/ENGOT-ov25).

Journal of the National Cancer Institute·2026
Same author

Independent recruitment of enzymes for phenylpropanoid sucrose ester biosynthesis in Polygala tenuifolia.

The Plant journal : for cell and molecular biology·2026
Same author

The selenium-enriched <i>Rhodotorula mucilaginosa</i> JAASRY1 improved oxidative stress during the aging process via the gut-liver-brain axis.

Frontiers in microbiology·2026
Same author

Video-based gait analysis for clinical monitoring of genotype-specific functional patterns in osteogenesis imperfecta.

BMC musculoskeletal disorders·2026
Same author

Roseburia intestinalis-derived extracellular vesicles alleviate osteoporosis through gut microbiota-regulated histidylleucine via Akt/FOXO1 signaling.

Communications biology·2026
Same author

RE: Clinician- and facility-level factors associated with chemotherapy dose reductions in stages I-IIIA breast cancer.

Journal of the National Cancer Institute·2026

相关实验视频

Updated: May 10, 2026

Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace
09:11

Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace

Published on: August 8, 2019

5.8K

类别级6D对象姿势估计与形状变形用于机器人抓手检测.

Sheng Yu, Di-Hua Zhai, Yuyin Guan

    IEEE transactions on neural networks and learning systems
    |November 14, 2023
    PubMed
    概括

    CatDeform通过弥合合成与真实数据之间的差距,有效地估计了用于机器人抓取的6D对象姿势. 这种新型网络使用基于变压器的融合和注意力实现了最先进的性能,最大限度地减少了对大型现实世界数据集的依赖.

    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 计算机视觉 计算机视觉
    • 机器学习 机器学习

    背景情况:

    • 类别级的6D对象姿势估计对于机器人抓取检测至关重要.
    • 合成到真实数据领域的差距限制了模型的可转移性,阻碍了现实世界的应用.
    • 大规模的真实世界数据集的获取是昂贵的,耗时的.

    研究的目的:

    • 介绍CatDeform,一个用于类别级对象构成估计的新型网络.
    • 能够在合成数据上进行有效的模型训练,以获得卓越的现实世界性能.
    • 减少对大量现实世界注释数据集的依赖.

    主要方法:

    • 基于变压器的融合模块用于多源信息集成和增强预测.
    • 基于变压器的注意模块用于在几何和特征方面变形先前的点云.
    • 监督学习和自我监督培训的双分支网络,以弥合合成和真实数据之间的差距.

    主要成果:

    • CatDeform在使用主要是合成训练数据的真实数据集上表现出强的表现.
    • 在CAMERA25和REAL275数据集上的自我监督和监督训练范式中,超越了最先进的方法.
    • 在现实世界机器人实验中实现高精度的姿势估计和提高掌握成功率.

    更多相关视频

    Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
    07:52

    Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

    Published on: July 10, 2019

    14.2K
    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
    09:41

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

    Published on: April 21, 2023

    1.6K

    相关实验视频

    Last Updated: May 10, 2026

    Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace
    09:11

    Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace

    Published on: August 8, 2019

    5.8K
    Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
    07:52

    Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

    Published on: July 10, 2019

    14.2K
    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
    09:41

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

    Published on: April 21, 2023

    1.6K

    结论:

    • CatDeform有效地解决了对象姿势估计中的合成与真实领域差距.
    • 拟议的基于变压器的方法使得可靠和准确的姿势估计能够减少对真实数据的依赖.
    • CatDeform显示了在实际应用中增强机器人掌握能力的巨大潜力.