Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Correlations02:20

Correlations

36.6K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
36.6K
Correlation and Causation01:27

Correlation and Causation

42.9K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
42.9K
Correlation01:09

Correlation

15.2K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
15.2K
Correlation and Regression00:53

Correlation and Regression

3.5K
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...
3.5K
Coefficient of Correlation01:12

Coefficient of Correlation

8.7K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
8.7K
Correlation of Experimental Data01:23

Correlation of Experimental Data

491
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
491

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Image authentication with exclusive-OR operated optical vortices.

Journal of the Optical Society of America. A, Optics, image science, and vision·2025
Same author

Extension of physical activity recognition with 3D CNN using encrypted multiple sensory data to federated learning based on multi-key homomorphic encryption.

Computer methods and programs in biomedicine·2023
Same author

Unsupervised Learning of Disentangled Representation via Auto-Encoding: A Survey.

Sensors (Basel, Switzerland)·2023
Same author

Tailored dual polarization encryption-coherence modulation-based decryption scheme for a predefined uniformly distributed noisy output image.

Optics express·2022
Same author

A Survey of NOMA for VLC Systems: Research Challenges and Future Trends.

Sensors (Basel, Switzerland)·2022
Same author

Behavioral Analysis and Individual Tracking Based on Kalman Filter: Application in an Urban Environment.

Sensors (Basel, Switzerland)·2021
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

Related Experiment Video

Updated: Feb 12, 2026

Lens Transplantation in Zebrafish and its Application in the Analysis of Eye Mutants
10:39

Lens Transplantation in Zebrafish and its Application in the Analysis of Eye Mutants

Published on: June 1, 2009

11.5K

One lens optical correlation: application to face recognition.

Maher Jridi, Thibault Napoléon, Ayman Alfalou

    Applied Optics
    |April 1, 2018
    PubMed
    Summary
    This summary is machine-generated.

    A new optical correlation scheme simplifies setups by making decisions in the Fourier plane, reducing hardware needs and improving face recognition accuracy.

    More Related Videos

    Correlative Optical Spectroscopy and Mass Spectrometry Imaging Methodology to Visualise Drug Distribution in a Soft Tissue Section
    07:05

    Correlative Optical Spectroscopy and Mass Spectrometry Imaging Methodology to Visualise Drug Distribution in a Soft Tissue Section

    Published on: June 20, 2025

    1.4K
    Simulating the Mechanics of Lens Accommodation via a Manual Lens Stretcher
    05:14

    Simulating the Mechanics of Lens Accommodation via a Manual Lens Stretcher

    Published on: February 23, 2018

    7.2K

    Related Experiment Videos

    Last Updated: Feb 12, 2026

    Lens Transplantation in Zebrafish and its Application in the Analysis of Eye Mutants
    10:39

    Lens Transplantation in Zebrafish and its Application in the Analysis of Eye Mutants

    Published on: June 1, 2009

    11.5K
    Correlative Optical Spectroscopy and Mass Spectrometry Imaging Methodology to Visualise Drug Distribution in a Soft Tissue Section
    07:05

    Correlative Optical Spectroscopy and Mass Spectrometry Imaging Methodology to Visualise Drug Distribution in a Soft Tissue Section

    Published on: June 20, 2025

    1.4K
    Simulating the Mechanics of Lens Accommodation via a Manual Lens Stretcher
    05:14

    Simulating the Mechanics of Lens Accommodation via a Manual Lens Stretcher

    Published on: February 23, 2018

    7.2K

    Area of Science:

    • Optics and Photonics
    • Digital Signal Processing
    • Computer Vision

    Background:

    • Traditional Vander Lugt Correlator (VLC) optical setups are widely used but complex.
    • Existing VLC systems require multiple lenses and inverse Fourier transforms, increasing hardware demands.

    Purpose of the Study:

    • To propose a simplified optical correlation scheme.
    • To enable decision-making directly in the Fourier plane, eliminating the need for an inverse Fourier transform.
    • To reduce computational complexity and hardware resource requirements.

    Main Methods:

    • A novel correlation scheme is presented where the Fourier plane serves as the decision plane.
    • The offline phase and decision metric are re-evaluated for performance optimization.
    • Digital multiplication with the correlation filter is employed for adaptability.
    • Performance is assessed through hardware resource analysis and experimental face verification.

    Main Results:

    • The proposed scheme significantly reduces the number of arithmetic operators (nearly 100x fewer).
    • Experimental results show comparable or superior accuracy to traditional methods in face verification.
    • The new method demonstrates enhanced sensitivity to face orientation compared to traditional schemes.
    • The scheme is amenable to digital and optical implementation, facilitating broad integration.

    Conclusions:

    • The simplified optical correlation scheme offers significant advantages in hardware efficiency and performance.
    • Direct decision-making in the Fourier plane reduces computational load and complexity.
    • The proposed method is a promising advancement for face identification and other correlation-based applications.