RETRACTED: Uncalibrated dynamic visual servoing via multivariate adaptive regression splines and improved incremental

Related Experiment Video

Updated: Jan 28, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.4K

Zhiyu Zhou1, Ruoxi Zhang1, Zefei Zhu2

  • 1School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.

ISA Transactions
|March 11, 2019
PubMed

Keywords:
Image-based visual servoIncremental extreme learning machineMultivariate adaptive regression splinesRandom reduced kernel regularization

More Related Videos

Visualizing Visual Adaptation04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

9.6K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.7K

Related Concept Videos

Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.9K
Clot Retraction and Fibrinolysis01:16

Clot Retraction and Fibrinolysis

After a fibrin clot is formed, the next step is clot retraction, a vital process facilitated by platelet contractile proteins, such as actin and myosin. These proteins pull the fibrin strands closer together and condense the clot. This action reduces the size of the clot, creating a smaller, denser structure that effectively seals off the damaged vessel. Clot retraction consolidates the clot and helps with wound healing by bringing the edges of the damaged blood vessel closer together.
8.8K
Multiple Regression01:25

Multiple Regression

Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.9K
Correlation and Regression00:53

Correlation and Regression

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...
3.4K
Regression Analysis01:11

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.4K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.5K