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

相关实验视频

Updated: Jul 1, 2025

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

9.8K

基于深度神经网络的阶段调制连续波LiDAR.

Hao Zhang1,2, Yubing Wang1, Mingshi Zhang3

  • 1State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
概括
此摘要是机器生成的。

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

Strain-Compensated Quantum Well Asymmetric Waveguide Edge-Emitting Laser Operating at 730 nm.

Sensors (Basel, Switzerland)·2025
Same author

Active Region Mode Control for High-Power, Low-Linewidth Broadened Semiconductor Optical Amplifiers for Light Detection and Ranging.

Sensors (Basel, Switzerland)·2024
Same author

Semiconductor Optical Amplifiers with Wide Gain Bandwidth and Enhanced Polarization Insensitivity Based on Tensile-Strained Quantum Wells.

Sensors (Basel, Switzerland)·2024
Same author

Low-Polarization, Broad-Spectrum Semiconductor Optical Amplifiers.

Nanomaterials (Basel, Switzerland)·2024
Same author

Adjoint Algorithm Design of Selective Mode Reflecting Metastructure for BAL Applications.

Nanomaterials (Basel, Switzerland)·2024
Same author

Advances in Semiconductor Lasers Based on Parity-Time Symmetry.

Nanomaterials (Basel, Switzerland)·2024
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

一种新的深度神经网络方法精确地从相调连续波 (PhMCW) LiDAR中提取飞行时间数据,即使信号与噪声比率 (SNR) 较低. 这推动了LiDAR技术的发展,用于精确的物体检测和3D重建.

科学领域:

  • 光学和光子学 在光学和光子学.
  • 计算机视觉和机器学习
  • 机器人技术和自主系统

背景情况:

  • 光探测和测距 (LiDAR) 提供高精度和分辨率,对于各种应用至关重要.
  • 阶段调制连续波 (PhMCW) LiDAR提供了低功耗和高精度等优势.
  • 信号与噪声比 (SNR) 的降解严重影响了LiDAR中传统的飞行时间提取方法.

研究的目的:

  • 引入一种新的深度神经网络 (DNN) 方法,用于在PhMCW LiDAR中进行可靠的飞行时间测量.
  • 在不同距离分辨率和低SNR条件下评估DNN方法的性能.
  • 为了证明DNN在模拟复杂场景中重建详细的3D点云的能力.

主要方法:

  • 开发了一个深度神经网络模型,旨在直接处理LiDAR信号.
  • 模拟6米射程场景,包括各种物体 (车辆,树,房子) 和背景.
  • 分析识别准确性和性能指标在0.1米距离分辨率和SNR低至2.

主要成果:

  • 拟议的DNN方法在具有挑战性的低SNR (2) 和0.1米分辨率下实现了81.4%的识别精度.
  • 模拟的点云重建显示了高保真度,清晰的对象轮和恢复的特征.
关键词:
深度神经网络是一个神经网络.在这里,我们可以看到LIDAR LIDAR LIDAR.阶段调节的连续波持续波.脉冲的宽度 脉冲的宽度

更多相关视频

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.2K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

531

相关实验视频

Last Updated: Jul 1, 2025

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

9.8K
Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.2K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

531
  • 精确的距离测量 (4.73厘米,6.00厘米,7.19厘米) 证明了该方法的卓越性能.

    • 结论:

    • 深度神经网络为处理LiDAR信号和提取飞行时间提供了可行和有效的解决方案.
    • 这项工作代表了神经网络用于直接LiDAR信号处理和飞行时间提取的首次应用.
    • 在低SNR环境和复杂场景中,DNN方法显示了改善LiDAR性能的巨大潜力.