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

Masking and Demasking Agents01:19

Masking and Demasking Agents

2.6K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
2.6K
Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

242
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
242
Prosopagnosia01:24

Prosopagnosia

244
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...
244
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

519
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
519

You might also read

Related Articles

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

Sort by
Same author

Selective multimodal deep learning for reliable breast cancer subtype classification from histopathology and genomic data.

Medical engineering & physics·2026
Same author

A Multimodel-Based Screening Framework for C-19 Using Deep Learning-Inspired Data Fusion.

IEEE journal of biomedical and health informatics·2024
Same author

Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention.

Frontiers in radiology·2024
Same author

Robust cardiac segmentation corrected with heuristics.

PloS one·2023
Same author

Efficient Breast Cancer Classification Network with Dual Squeeze and Excitation in Histopathological Images.

Diagnostics (Basel, Switzerland)·2023
Same author

The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 3, 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

Fusion Methods for Face Presentation Attack Detection.

Faseela Abdullakutty1, Pamela Johnston1, Eyad Elyan1

  • 1School of Computing, Robert Gordon University, Aberdeen AB10 7AQ, UK.

Sensors (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

This study enhances face recognition security by fusing deep learning features with traditional color and texture analysis for better presentation attack detection. Integrating diverse features significantly improves accuracy in identifying spoofing attempts.

Keywords:
deep learningface presentation attacksfeature-fusion

More Related Videos

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face
08:15

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face

Published on: January 7, 2019

7.0K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.0K

Related Experiment Videos

Last Updated: Sep 3, 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
Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face
08:15

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face

Published on: January 7, 2019

7.0K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.0K

Area of Science:

  • Computer Science
  • Biometrics
  • Artificial Intelligence

Background:

  • Face presentation attacks (PA) pose a significant threat to face recognition (FR) systems, as they are easily executed and challenging to detect.
  • Existing methods, including deep learning and traditional feature engineering, show effectiveness but may not fully capture all relevant discriminative information.
  • The optimal approach for PA detection remains an open question regarding feature representation.

Purpose of the Study:

  • To investigate whether deep neural networks adequately learn traditional low-level features for optimal presentation attack detection.
  • To propose and evaluate a simple feature-fusion method combining deep learning features with traditional color and texture features.
  • To demonstrate the benefits of an enriched feature space for improving PA detection rates.

Main Methods:

  • A feature-fusion strategy was developed to integrate features from pre-trained deep learning models with traditional color and texture features.
  • The proposed method was evaluated on three public datasets: CASIA, Replay Attack, and SiW.
  • Performance was assessed based on detection rates achieved by the fused feature space.

Main Results:

  • Extensive experiments demonstrated that enriching the feature space by fusing deep learning and traditional features significantly improves detection rates.
  • The proposed simple feature-fusion method proved effective in enhancing the performance of presentation attack detection.
  • Results confirm the benefit of combining diverse feature types for robust PA detection.

Conclusions:

  • Combining features from deep learning models with traditional color and texture features is beneficial for improving face presentation attack detection.
  • The proposed feature-fusion method offers a practical approach to enhance the security of face recognition applications against spoofing.
  • Future research should explore novel characterizing features and advanced fusion strategies for even more robust PA detection.