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

相关概念视频

Thin-Layer Chromatography (TLC): Overview01:11

Thin-Layer Chromatography (TLC): Overview

1.3K
Thin-layer chromatography (TLC) is a chromatography technique that separates compounds based on their polarity. TLC typically uses polar silica gel, a form of silicon dioxide, as the stationary phase. The silica gel contains hydroxyl (OH) groups on its surface, which form hydrogen bonds with polar compounds, influencing their adhesion to the stationary phase.
To begin the analysis, a mixture of compounds is spotted on the starting line on the TLC plate using a thin capillary. The bottom of the...
1.3K

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

Tumor cell intrinsic and extrinsic features predict prognosis in estrogen receptor positive breast cancer.

PLoS computational biology·2022
Same author

Comparison of the diagnostic efficacy of <sup>68</sup> Ga-FAPI-04 PET/MR and <sup>18</sup>F-FDG PET/CT in patients with pancreatic cancer.

European journal of nuclear medicine and molecular imaging·2022
Same author

Addressing Extreme Propensity Scores in Estimating Counterfactual Survival Functions via the Overlap Weights.

American journal of epidemiology·2022
Same author

68 Ga-FAPI-04 Versus 18 F-FDG PET/CT in a Case of Peutz-Jeghers Syndrome.

Clinical nuclear medicine·2022
Same author

Fatty acid synthase (Fasn) inhibits the expression levels of immune response genes via alteration of alternative splicing in islet cells.

Journal of diabetes and its complications·2022
Same author

Risk Factors and Outcome Variables of Cardiorenal Syndrome Type 1 in Acute Myocardial Infarction Patients.

International journal of general medicine·2022
Same journal

Therapeutic potential of crude protein extracts from two Egyptian freshwater snails Lanistes carinatus and Bellamya unicolor.

Scientific reports·2026
Same journal

Microbial contamination of donor corneas and post-keratoplasty endophthalmitis: a comparison between Japanese and U.S. eye banks using cold storage.

Scientific reports·2026
Same journal

Prevalence and contributing factors of virological non-suppression among adult patients on first-line antiretroviral therapy in tertiary hospitals in Ethiopia.

Scientific reports·2026
Same journal

An in vitro comparison of color stability between alkasite and different restorative materials in various staining solutions.

Scientific reports·2026
Same journal

Toward accessible mRNA LNP formulation: systematic evaluation of mixing strategies and key parameters.

Scientific reports·2026
Same journal

A network analysis of personality traits, mentalizing, and psychological health in Chinese college students.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: Jun 8, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.8K

一个基于RIME优化和最佳值的车道检测算法.

Shuang Zhai1, Xiao Zhao1, Guoming Zu1

  • 1College of Computer Science and Engineering, Changchun University of Technology, Changchun, 130012, China.

Scientific reports
|November 8, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的车道检测算法,用于挑战性道路条件,通过整合/冰优化和最佳值来实现更安全的自动驾驶,将准确性提高到93.87%.

关键词:
图像细分 图像细分 图像细分车道线路检测 车道线路检测在 RIME 优化算法中,

更多相关视频

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K

相关实验视频

Last Updated: Jun 8, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.8K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K

科学领域:

  • 计算机视觉 计算机视觉
  • 自主驾驶系统 自主驾驶系统
  • 图像处理 图像处理

背景情况:

  • 复杂的道路条件,如和冰,显著降低了车道线路检测性能.
  • 现有的算法与低可见度和干扰作斗争,影响自动驾驶汽车的安全性.

研究的目的:

  • 开发一个强大的车道线路检测算法,适应恶劣的天气和道路条件.
  • 为了提高自动驾驶系统的车道检测的准确性和效率.

主要方法:

  • 一个新的算法,将/冰优化与最佳值相结合.
  • 使用Retinex理论进行预处理,以减少噪音和保存细节.
  • 通过增强的OTSU值与帐映射进行细分.
  • 鸟视图转换和适应式滑动窗口用于特征识别.
  • 使用RANSAC与抛物线模型进行车道线路装配.

主要成果:

  • 实现了93.87%的车道线路检测准确率,超过了传统的Hough转换 (43.2%) 和组合方法 (89.16%).
  • 与类似的图像分割算法相比,在值计算错误和计算效率方面表现出显著的优势.
  • 在复杂的道路条件下对干扰因素表现出了显著的坚固性.

结论:

  • 拟议的算法有效地解决了由复杂的道路条件引起的低车道线路检测率的挑战.
  • 该方法提供了卓越的准确性和稳定性,对于可靠的自动驾驶系统至关重要.
  • 公开可用的代码促进了智能交通系统的进一步研究和开发.