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

Improving Translational Accuracy02:07

Improving Translational Accuracy

11.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.9K
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

2.4K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
2.4K
Correlation and Regression00:53

Correlation and Regression

2.0K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
2.0K
Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

2.5K
In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
2.5K
Adaptability of Cytoskeletal Filaments01:12

Adaptability of Cytoskeletal Filaments

3.9K
The cytoskeleton is a complex dynamic structure performing varied functions based on cellular requirements. The adaptability of the individual filaments in the cytoskeleton determines their ability to perform various functions within the cell. It can undergo rapid reorganization during processes like cell division or remain stable for several hours as in the interphase. The adaptability of these filaments depends on stringent regulatory mechanisms. The microfilament and microtubules of the...
3.9K
Point and Frameshift Mutations01:30

Point and Frameshift Mutations

101
Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
101

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

Co-existence of clinical high-risk for psychosis and bipolar disorder: a multi-dimensional psychopathological analysis.

BMC psychiatry·2026
Same author

Clozapine-induced Myocarditis in Korea: Analysis of a Nationwide Database and Comparison to Other Countries.

Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology·2026
Same author

Clozapine-related neutropenia and agranulocytosis in Korea: 2025 update for rethinking the role of monitoring system.

Therapeutic advances in psychopharmacology·2026
Same author

Long-acting injectable vs. oral antipsychotics during electroconvulsive therapy in psychosis: a retrospective comparative study.

International clinical psychopharmacology·2026
Same author

Neutrophil- and Platelet-to-Lymphocyte Ratios as Predictive Markers for Capsular Contracture after Immediate Implant-Based Reconstruction.

Plastic and reconstructive surgery·2026
Same author

Transformer-augmented dual-branch siamese tracker with confidence-aware regression and adaptive template updating.

Scientific reports·2026

相关实验视频

Updated: Sep 18, 2025

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.7K

通过自适应式混合模型学习多规范化的突变感知相关性过器,用于通过自适应式混合模型对象跟踪.

Sathiyamoorthi Arthanari1, Jae Hoon Jeong1, Young Hoon Joo1

  • 1School of IT Information and Control Engineering, Kunsan National University, 558 Daehak-ro, Gunsan-si, Jeonbuk 54150, Republic of Korea.

Neural networks : the official journal of the International Neural Network Society
|June 25, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种用于对象跟踪的多规范化突变感知相关性过器 (MRMACF). 该MRMACF方法有效地处理外观突变和目标扭曲,在具有挑战性的场景中提高追踪精度和可靠性.

关键词:
和自适应式混合动力模型.相关性过器是一个相关性过器.突变意识的方法.对象追踪器可以追踪物体.周围意识的方法周围意识的方法时间规范化的时间规范化.

更多相关视频

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.8K
Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

4.9K

相关实验视频

Last Updated: Sep 18, 2025

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.7K
A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

7.8K
Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

4.9K

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 区分相关过器 (DCF) 对于对象跟踪是有效的,但与外观突变,过器退化和目标扭曲作斗争.
  • 由于这些挑战,现有的DCF追踪器面临性能下降,需要提高稳定性.

研究的目的:

  • 引入一种新的多规范化突变感知相关性过器 (MRMACF),以解决基于DCF的对象跟踪的局限性.
  • 为了增强追踪器对外观变化,过器退化和目标扭曲的弹性.

主要方法:

  • 开发了一种具有适应性混合模型和突变威胁机制的突变意识策略,以处理外观突变和过器退化.
  • 实施了改进的稀疏空间特征选择,结合行/列方法来解决目标扭曲.
  • 引入了周围意识的方法,以利用上下文信息并防止过器偏差.

主要成果:

  • 与基准数据集上的现代追踪器相比,MRMACF方法显示出更高的性能.
  • 在OTB-2015数据集中实现了最高的性能,DP得分为93.2%和AUC得分为69.8%.

结论:

  • 拟议的MRMACF方法通过有效地减轻外观突变,过器退化和目标扭曲,显著提高了对象跟踪性能.
  • 对于具有挑战性的对象跟踪任务,MRMACF提供了强大而高效的解决方案.