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 Experiment Videos

Improved minimum squared error algorithm with applications to face recognition.

Qi Zhu1, Zhengming Li, Jinxing Liu

  • 1Bio-Computing Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.

Plos One
|August 13, 2013
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

You might also read

Related Articles

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

Sort by
Same author

Correlation between reproductive hormone levels and genetic abnormalities in patients with non-obstructive azoospermia and oligospermia.

Translational andrology and urology·2026
Same author

Association of Oral Contraceptives with Adverse Pregnancy Outcomes: A Mendelian Randomization and Colocalization Study.

Current medicinal chemistry·2026
Same author

Genital-prioritized attentional bias in lifelong premature ejaculation: behavioral evidence from eye-tracking and machine learning.

International journal of impotence research·2026
Same author

Attentional Avoidance of Sexual Cues in Psychogenic Erectile Dysfunction: An Eye-Tracking and Machine Learning Study.

Andrology·2026
Same author

Parental academic involvement and academic engagement in adolescence: moderating effects of growth mindset across diverse educational contexts.

BMC psychology·2026
Same author

Prognostic Value of Estimated Glomerular Filtration Rate in Older Patients With Acute Coronary Syndrome.

Reviews in cardiovascular medicine·2026
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles

An improved Minimum Squared Error based Classification (IMSEC) method offers better accuracy for individual samples. This tailored approach enhances classification performance compared to standard MSEC, particularly in face recognition tasks.

Area of Science:

  • Computer Science
  • Machine Learning
  • Pattern Recognition

Background:

  • Traditional Minimum Squared Error based Classification (MSEC) uses a single model for all samples.
  • This universal model may not be optimal for individual test samples, limiting classification accuracy.
  • Face recognition is a critical application area where classification accuracy is paramount.

Purpose of the Study:

  • To develop an improved Minimum Squared Error based Classification (IMSEC) method.
  • To enhance classification accuracy by tailoring models to individual test samples.
  • To evaluate the performance of IMSEC against MSEC and other state-of-the-art methods in face recognition.

Main Methods:

  • The proposed IMSEC method first identifies potential classes for a given test sample.

Related Experiment Videos

  • It then constructs a Minimum Squared Error (MSE) model using training data from these identified potential classes.
  • The method was applied to face recognition tasks using multiple benchmark datasets.

    • Main Results:

    • IMSEC demonstrated superior classification accuracy compared to the standard MSEC method.
    • The proposed IMSEC method also outperformed other existing state-of-the-art techniques.
    • Experimental results across several datasets consistently showed the effectiveness of IMSEC.

    Conclusions:

    • The IMSEC method provides a more accurate and personalized classification approach.
    • Tailoring classification models to individual samples significantly improves performance.
    • IMSEC represents a promising advancement for face recognition and other classification applications.