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

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

Reduced-intensity conditioning therapy with fludarabine, idarubicin, busulfan and cytarabine for allogeneic hematopoietic stem cell transplantation in acute myeloid leukemia and myelodysplastic syndrome.

Leukemia research·2013
Same author

Effects of 3, 5, 3'-triiodothyronine (t3) and follicle stimulating hormone on apoptosis and proliferation of rat ovarian granulosa cells.

The Chinese journal of physiology·2013
Same author

Cardiogenic shock from acute ST-segment elevation myocardial infarction induced by severe multivessel coronary vasospasm.

European heart journal·2013
Same author

[Comparative study on effects of electroacupuncture stimulation of Shenmen (HT 7) and Taiyuan (LU 9) on P 300 of event-related potentials and brain electrical activity mapping in healthy young adults].

Zhen ci yan jiu = Acupuncture research·2013
Same author

MiR-215 modulates gastric cancer cell proliferation by targeting RB1.

Cancer letters·2013
Same author

Low glucose utilization and neurodegenerative changes caused by sodium fluoride exposure in rat's developmental brain.

Neuromolecular medicine·2013

相关实验视频

Updated: Jul 12, 2025

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

14.9K

混合融合:一种高效的多模式数据融合框架,用于3D对象检测和跟踪.

Cheng Zhang, Hai Wang, Long Chen

    IEEE transactions on neural networks and learning systems
    |November 1, 2023
    PubMed
    概括

    本研究介绍了MixedFusion,这是一种用于智能互联汽车 (ICV) 的新多式联网数据融合框架. 混合融合增强了环境感知和3D物体检测和跟踪,特别是在恶劣的天气条件下.

    科学领域:

    • 计算机视觉 计算机视觉
    • 机器人技术 机器人技术 机器人技术
    • 人工智能的人工智能

    背景情况:

    • 环境感知对于智能互联汽车 (ICV) 的安全运行至关重要.
    • 目前用于ICV的多式联动数据融合方法在传感器数据利用和融合策略方面面临挑战,特别是在恶劣的天气中.
    • 这些局限性阻碍了安全自动驾驶所需的全面感知.

    研究的目的:

    • 提出一种新的多式联运数据融合框架,即混合融合,以克服现有方法的局限性.
    • 加强多式联运传感器数据的利用和互补融合,以改善环境感知.
    • 在具有挑战性的天气条件下显著提高3D物体检测和跟踪的性能.

    主要方法:

    • 开发了混合融合框架,结合了两个创新的融合策略:高层次语义指导 (HLSG) 和多重点匹配 (MPM).
    • 设计了融合策略,以有效利用和补充来自各种传感器的数据.
    • 在基准数据集 (nuScenes和K-radar) 上进行了广泛的实验.

    主要成果:

    • 混合融合展示了多式联运数据的高效利用.
    • 该框架实现了互补的融合,增强了数据集成.
    • 在3D物体检测和跟踪性能中观察到显著的改进.

    更多相关视频

    FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis
    10:02

    FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

    Published on: December 24, 2014

    11.8K
    Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
    13:02

    Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

    Published on: February 27, 2016

    12.3K

    相关实验视频

    Last Updated: Jul 12, 2025

    A Protocol for Real-time 3D Single Particle Tracking
    10:16

    A Protocol for Real-time 3D Single Particle Tracking

    Published on: January 3, 2018

    14.9K
    FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis
    10:02

    FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

    Published on: December 24, 2014

    11.8K
    Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
    13:02

    Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

    Published on: February 27, 2016

    12.3K

    结论:

    • 拟议的混合融合框架有效地解决了现有的融合感知方法的局限性.
    • 混合融合提供了一个强大的解决方案,用于提高智能互联汽车的环境感知.
    • 该框架特别有望改善ICV在恶劣天气条件下的安全性和可靠性.