Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Inhalation of Environmental Polystyrene Micro/Nanoplastics Induces Pulmonary Toxicity and Synergistically Exacerbates Acute Lung Injury in Male Mice.

Journal of applied toxicology : JAT·2026

Same author

The relationship between nutritional management and prognosis in children on prolonged mechanical ventilation.

Journal of pediatric gastroenterology and nutrition·2026

Same author

SLC39A1 sustains mitochondrial integrity in alveolar epithelium during acute lung injury.

Experimental cell research·2026

Same author

Beyond Net Ultrafiltration Rate: A Precision Fluid Management Paradigm Integrating Three Key Parameters for Pediatric Continuous Renal Replacement Therapy.

Critical care explorations·2026

Same author

Association between platelet-albumin-bilirubin score and 30-day in-hospital mortality in patients with sepsis: evidence from a large database and machine learning modeling.

BMC infectious diseases·2026

Same author

Clinical characteristics and inflammatory response of adenovirus viremia in children with severe adenoviral pneumonia: a prospective cohort study.

BMC infectious diseases·2026

Search research articles

Related Experiment Video

Updated: Apr 30, 2026

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Published on: September 26, 2019

Clustering-based discriminant analysis for eye detection.

Shuo Chen, Chengjun Liu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|May 9, 2014

Summary

This summary is machine-generated.

This study introduces three clustering-based discriminant analysis (CDA) models to improve feature extraction for classification tasks. These models enhance performance, particularly in two-class problems, and lead to better eye detection.

More Related Videos

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Related Experiment Videos

Last Updated: Apr 30, 2026

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Published on: September 26, 2019

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Area of Science:

Computer Vision
Machine Learning
Pattern Recognition

Background:

Fisher linear discriminant analysis (FLDA) may struggle with feature extraction in certain classification problems.
Effective feature extraction is crucial for accurate pattern recognition and classification tasks.

Purpose of the Study:

To propose novel clustering-based discriminant analysis (CDA) models to overcome limitations of traditional FLDA.
To enhance feature extraction capabilities for improved classification performance, especially in two-class scenarios.
To develop and evaluate a CDA-based method for accurate eye detection.

Main Methods:

Developed three CDA models: CDA-1 using k-means clustering for scatter matrices, and CDA-2/CDA-3 using nonparametric scatter matrices.
CDA-2 computes nonparametric scatter matrices locally, while CDA-3 computes them globally.
Applied the proposed CDA models to an eye detection task.

Main Results:

The proposed CDA models demonstrate feasibility and effectiveness in feature extraction.
Experiments show improved eye detection performance compared to existing state-of-the-art methods.
The nonparametric nature of CDA-2 and CDA-3 preserves crucial classification structures.

Conclusions:

The three proposed CDA models offer a viable alternative to traditional FLDA for improved classification.
The CDA-based approach significantly enhances eye detection accuracy.
The developed methods show promise for various pattern recognition applications.