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

4.2K
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...
4.2K

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

PKMYT1 in Cancer: Beyond Cell Cycle Checkpoints to Context-Dependent Therapeutic Vulnerability.

Genes, chromosomes & cancer·2026
Same author

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care.

Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence·2026
Same author

Cross-kingdom metabolic interactions govern Candida albicans overgrowth and colitis progression.

Cell host & microbe·2026
Same author

Trim45 promotes the occurrence and development of cervical cancer by inhibiting the cGAS/STING signaling pathway.

Integrative biology : quantitative biosciences from nano to macro·2026
Same author

Microbial phosphoketolase promotes histone lactylation to improve anti-TNF therapy efficacy in inflammatory bowel disease.

Cell metabolism·2026
Same author

Insulin and IGF signaling in the brain: multilevel regulation of synaptic and network homeostasis.

Frontiers in endocrinology·2026
Same journal

A Dataset with Bilingual TV Commands for Silent Speech Interfaces Using Electroencephalographic Signals.

Scientific data·2026
Same journal

BEAMSTER: Brain mEtAstases segMentation for STEreotactic Radiotherapy, A Retrospective MRI Dataset with Expert Segmentations.

Scientific data·2026
Same journal

Chromosomal-level genome assembly of Tetraponera attenuata (Hymenoptera: Formicidae).

Scientific data·2026
Same journal

High quality Chromosome-scale Genome Assembly of Phlebotomus perniciosus, a Vector of Zoonotic Leishmaniasis.

Scientific data·2026
Same journal

Characterisation Data of common pharmaceutical excipient Powders and Tablets for Formulation Development.

Scientific data·2026
Same journal

Chinese Electric Vehicle Policy Database: A Dataset of Policy Goals, Instruments, and Supply Chain Stages.

Scientific data·2026
查看所有相关文章

相关实验视频

Updated: Sep 15, 2025

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

177

作为占用和重建的场景:用于理解非结构化的场景的全面数据集

Long Chen1,2, Ruiqi Song1,3,2, Hangbin Wu4

  • 1Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.

Scientific data
|July 15, 2025
PubMed
概括
此摘要是机器生成的。

一个新的数据集解决了在非结构化环境中自动驾驶数据的缺乏问题. 它可以改善对不规则障碍物和道路表面的感知和规划,提高安全性和舒适性.

更多相关视频

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.1K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.9K

相关实验视频

Last Updated: Sep 15, 2025

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

177
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.1K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.9K

科学领域:

  • 机器人和人工智能 机器人和人工智能
  • 计算机视觉 计算机视觉
  • 自主系统 自主系统

背景情况:

  • 自动驾驶技术正在向大规模商业化迈进,安全和舒适是关键性能指标.
  • 当前的研究往往侧重于城市驾驶,忽视了带有不规则障碍物和道路波的非结构化场景.
  • 对于非结构化环境的现有数据集和研究很少,这限制了强大的自主系统的发展.

研究的目的:

  • 引入世界上第一个全面的基准数据集,用于在非结构化的场景中的感知.
  • 为了促进自动驾驶应用在城市环境之外的扩展.
  • 通过增强场景理解来提高自动驾驶的安全性和舒适性的研究.

主要方法:

  • 开发一种新的感知数据集,专门设计用于非结构化的场景.
  • 包含详细的注释,用于3D语义占用预测,以检测不规则的障碍.
  • 包括道路表面的升高重建,以描述道路表面的条件.

主要成果:

  • 该数据集为3D语义占用率预测和道路表面高度重建提供了全面的注释.
  • 包括轨迹和速度规划信息,以将感知与规划联系起来.
  • 使用最先进方法的实验验验证了数据集的有效性,并突出了任务挑战.

结论:

  • 这一数据集是推进非结构化环境中自动驾驶技术的宝贵资源.
  • 它解决了在复杂的越野场景中对数据的关键需求.
  • 该基准有助于对自动驾驶汽车的感知,规划和决策解释性进行研究.