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相关概念视频

Light Acquisition02:16

Light Acquisition

8.6K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.6K
Visual System01:26

Visual System

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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...
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相关实验视频

Updated: Sep 9, 2025

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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基于深度学习的图书馆智能照明系统的设计

Hong Wang1,2, Yingjie Sheng1,2, Yang Guo3,4

  • 1College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.

Scientific reports
|August 31, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了大学图书馆的智能照明系统,使用了改进的YOLOv5算法来准确地检测和定位人类. 这种智能系统提高了能源效率和图书馆的智能化.

关键词:
深度学习室内定位多层感知子模拟实验目标检测没有.

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Deep Neural Networks for Image-Based Dietary Assessment
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Building a Simple and Versatile Illumination System for Optogenetic Experiments
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科学领域:

  • 计算机视觉
  • 人工智能
  • 智能系统工程

背景情况:

  • 目前的大学图书馆照明系统的智能性较低, 能耗较高.
  • 需要自动化和适应性照明解决方案来改善用户体验并减少能源浪费.

研究的目的:

  • 设计和实施基于分区自主控制的大学图书馆智能照明解决方案.
  • 增强人类目标检测和空间定位准确性以适应照明.

主要方法:

  • 一个改进的YOLOv5算法,包含一个坐标注意力机制和深度可分离的卷积,用于人类目标检测.
  • 一种多层感知子 (MLP) 模型,用于将二维人类坐标映射到三维空间定位.
  • 在YOLOv5中优化边界框回归损失函数.

主要成果:

  • 在人体检测中达到91.4%的平均精度 (mAP).
  • 展示了图书馆空间内多个人的快速准确定位.
  • 实验结果显示,与基线方法相比,平均精度增加了6. 9%.

结论:

  • 拟议的智能照明系统有效地进行人体检测和定位.
  • 该系统为学术图书馆开发智能照明提供了实用且可参考的解决方案.
  • 这种方法显著提高了图书馆照明系统的智能和能源效率.