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

Association Areas of the Cortex01:21

Association Areas of the Cortex

6.5K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
6.5K
Parallel Processing01:20

Parallel Processing

269
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
269
Prosopagnosia01:24

Prosopagnosia

312
Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...
312

You might also read

Related Articles

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

Sort by
Same author

Gastric electrical stimulation reduces visceral sensitivity to gastric distention in healthy canines.

Autonomic neuroscience : basic & clinical·2010
Same author

Thickness-dependent autophobic dewetting of thin polymer films on coated substrates.

Langmuir : the ACS journal of surfaces and colloids·2010
Same author

[Results of randomized, multicenter, double-blind phase III trial of rh-endostatin (YH-16) in treatment of advanced non-small cell lung cancer patients].

Zhongguo fei ai za zhi = Chinese journal of lung cancer·2010
Same author

A SEMIPARAMETRIC MODEL FOR CLUSTER DATA.

Annals of statistics·2010
Same author

Bioactive electrospun scaffolds delivering growth factors and genes for tissue engineering applications.

Pharmaceutical research·2010
Same author

[Influence of inhaled corticosteroids on distribution of throat flora in children with bronchial asthma].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2010
Same journal

RETRACTION: Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
See all related articles

Related Experiment Video

Updated: Sep 28, 2025

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
09:49

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

14.3K

Research on Face Recognition Algorithm Based on Image Processing.

Yan Sun1, Zhenyun Ren1, Wenxi Zheng1

  • 1College of Information and Communication Engineering University, Harbin 150001, Heilongjiang, China.

Computational Intelligence and Neuroscience
|March 28, 2022
PubMed
Summary
This summary is machine-generated.

This study enhances face detection and recognition by improving the AdaBoost algorithm and introducing kernel-based methods like kernel principal component analysis (KPCA) and kernel Fisher discriminant analysis (KFDA). These advanced techniques improve accuracy and information security in network applications.

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.3K
Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.6K

Related Experiment Videos

Last Updated: Sep 28, 2025

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
09:49

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

14.3K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.3K
Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.6K

Area of Science:

  • Computer Science
  • Information Security
  • Artificial Intelligence

Background:

  • Network technology presents convenience but also security challenges.
  • Information security and accurate face identification are critical.
  • Traditional methods like AdaBoost and skin color detection have limitations.

Purpose of the Study:

  • To improve face detection and recognition accuracy.
  • To enhance network information security.
  • To evaluate advanced kernel-based methods for feature extraction.

Main Methods:

  • Improved AdaBoost algorithm for reduced false detection.
  • Kernel Principal Component Analysis (KPCA) and Kernel Fisher Discriminant Analysis (KFDA) utilizing kernel functions.
  • Zero-space based discriminant analysis for enhanced non-linear feature extraction.

Main Results:

  • The combined skin color + AdaBoost method shows improvement over individual methods.
  • KPCA and KFDA with polynomial kernels achieve high recognition rates, particularly at d=2.
  • The zero-space based KFDA method effectively utilizes discriminant information, boosting accuracy.

Conclusions:

  • Advanced kernel methods significantly improve face recognition accuracy.
  • The zero-space based approach enhances the extraction of non-linear features.
  • The proposed methods offer a more robust solution for secure face identification.