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相关概念视频

Vision01:24

Vision

59.2K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
59.2K
Olfaction01:25

Olfaction

47.9K
The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...
47.9K
Visual System01:26

Visual System

1.6K
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...
1.6K

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相关实验视频

Updated: Jan 7, 2026

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

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基于Resnet50和Elman网络的室内位置感知模型.

Pengjun Zhang1, Jie Mi2

  • 1School of Architectural Engineering, Hebei Vocational University of Industry and Technology, Shijiazhuang, China.

PloS one
|December 22, 2025
PubMed
概括

这项研究通过使用Resnet50改进特征提取并使用灰狼算法优化Elman网络来增强可见光室内定位. 这种新方法在室内位置传感方面实现了更高的准确性和稳定性.

科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 可见光室内定位提供高精度和低成本,但受到环境干扰和信号不稳定的影响.
  • 传统方法与多样化的特征表示和模型参数优化作斗争,导致定位错误.

研究的目的:

  • 为了提高可见光室内定位的准确性和稳定性.
  • 为了解决信号反干扰,特征表示和模型参数优化的局限性.

主要方法:

  • 使用Resnet50和特征金字塔概念开发了一种图像数据特征提取方法.
  • 设计了一个基于Elman网络的室内位置传感模型.
  • 提出了一个改进的灰狼优化算法来优化Elman网络参数.

主要成果:

  • 特性提取方法创建了一个更多样化的特性库 (同位数相似性接近0).
  • 改进的灰狼优化算法实现了比较算法更低的平均健身值.
  • 设计的感知模型在不同高度显示了3.04cm,3.57cm和3.19cm的平均误差,超过了对比模型.

结论:

  • 拟议的方法显著提高了特征表示的多样性.

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  • 优化的Elman网络模型在室内定位中实现了高精度和稳定性.
  • 这项研究为先进的室内位置传感提供了可行的技术途径.