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相关概念视频

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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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: Jan 8, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

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在图像检索系统中引入一种高效的特征提取方法.

Xiaojun Zhao1, Feng He2,3, Kun Li1

  • 1Special Equipment Inspection and Research Institute of Yunnan Province, Kunming, 650228, China.

Scientific reports
|December 12, 2025
PubMed
概括
此摘要是机器生成的。

这项研究通过结合纹理和颜色等多种功能来增强图像检索系统,使用黑洞优化 (BHO) 和模糊C-Means (FCM) 进行优化,以实现更快,更准确的图像搜索.

关键词:
黑洞优化黑洞的优化功能提取 功能提取模糊的C-意味着灰色级别的同时发生矩阵.图像检索 图像检索 图像检索

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
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相关实验视频

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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科学领域:

  • 计算机科学 计算机科学
  • 信息检索 信息检索
  • 人工智能的人工智能

背景情况:

  • 图像检索系统对于管理大型图像数据库和搜索引擎至关重要.
  • 目前的系统往往缺乏全面的功能,用于准确的图像描述和检索.
  • 高效的图像搜索提高了用户对信息的访问和整体搜索过程的效率.

研究的目的:

  • 通过使用更广泛的描述功能来提高图像检索系统的性能.
  • 通过优化功能选择来提高检索准确度和处理速度.

主要方法:

  • 图像特征被用四个类别来描述:纹理,颜色和相关图案.
  • 黑洞优化 (BHO) 算法用于最佳特征子集选择.
  • 模糊C-Means (FCM) 聚类用于基于所选特征的图像检索.

主要成果:

  • 拟议的方法在多个数据集中展示了显著的检索精度.
  • 在Corel1000中达到0.97的精度,在Brodatz中达到0.95,在ALOI数据库中达到0.94.
  • 整合BHO和FCM提高了准确性和处理速度.

结论:

  • 开发的方法有效地解决了当前图像检索系统的局限性.
  • 将全面的功能描述与优化选择相结合,可以显著提高检索性能.
  • 这种方法提供了一个强大的解决方案,以高效和准确的基于内容的图像检索.