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相关概念视频

Visual System01:26

Visual System

558
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
558

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相关实验视频

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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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实时室内可见光定位 (VLP) 使用长短期记忆神经网络 (LSTM-NN) 与主要组件分析 (PCA).

Yueh-Han Shu1, Yun-Han Chang1, Yuan-Zeng Lin1

  • 1Department of Photonics & Graduate Institute of Electro-Optical Engineering, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
概括

这项研究提高了室内定位精度,使用可见光. 将长期短期记忆神经网络 (LSTM-NN) 与主要组件分析 (PCA) 结合起来,可以显著减少定位错误,提高增强现实等应用的可靠性.

关键词:
长时间短期记忆神经网络 (LSTM-NN)主要组成部分分析 (PCA)可见光通信 (VLC) 是一种可见光通信.可见光定位 (VLP) 是指可见光的定位.

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相关实验视频

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科学领域:

  • 室内定位系统 室内定位系统
  • 光学无线通信的无线通信.
  • 机器学习用于本地化

背景情况:

  • 像AR/VR,物联网和AMR这样的新兴应用需要高精度的室内定位.
  • 可见光定位 (VLP) 为实时跟踪提供了一个有前途的解决方案.
  • 基于接收信号强度 (RSS) 的VLP很简单,但容易出现错误,特别是在细胞边界.

研究的目的:

  • 提出和演示一个实时的VLP系统,以提高准确性.
  • 使用LSTM-NN和PCA的组合来减轻定位错误.
  • 为了提高各种应用室内跟踪的可靠性.

主要方法:

  • 实现了实时可见光定位 (VLP) 系统.
  • 使用长期短期记忆神经网络 (LSTM-NN) 进行定位.
  • 集成主要组件分析 (PCA) 使用LSTM-NN来减少定位错误.

主要成果:

  • 仅使用LSTM-NN就实现了5.912厘米的平均定位误差.
  • 通过LSTM-NN和PCA将平均定位误差降低到1.806厘米,提高了69.45%.
  • 95%的实验数据显示LSTM-NN和PCA的误差小于5厘米,而单独使用LSTM-NN的误差大于15厘米.
  • 证明了系统能够预测移动接收器的方向和轨迹的能力.

结论:

  • 拟议的VLP系统有效地提高了室内定位准确度.
  • 结合LSTM-NN和PCA可显著提高精度,特别是在单元细胞边界.
  • 该系统显示了在苛刻的应用中实时跟踪和轨迹预测的潜力.