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

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

1.7K
Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...
1.7K
Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

1.5K
Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
1.5K
G-protein Coupled Receptors01:21

G-protein Coupled Receptors

132.0K
G-protein coupled receptors are ligand binding receptors that indirectly affect changes in the cell. The actual receptor is a single polypeptide that transverses the cell membrane seven times creating intracellular and extracellular loops. The extracellular loops create a ligand specific pocket which binds to neurotransmitters or hormones. The intracellular loops holds onto the G-protein.
132.0K
Spin–Spin Coupling: One-Bond Coupling01:17

Spin–Spin Coupling: One-Bond Coupling

1.5K
Coupling interactions are strongest between NMR-active nuclei bonded to each other, where spin information can be transmitted directly through the pair of bonding electrons. While nuclei polarize their electrons to the opposite spins, the bonding electron pair has opposite spins. Configurations with antiparallel nuclear spins are expected to be lower in energy. When coupling makes antiparallel states more favorable, J is considered to have a positive value. The one-bond coupling constant, 1J,...
1.5K
Couple01:29

Couple

998
A couple is a pair of parallel forces equal in magnitude but in opposite directions. The forces are separated by a perpendicular distance, known as the couple's arm. The couple causes a rotation force or moment that rotates the body about an axis perpendicular to the plane of the forces. The resulting moment is referred to as the couple moment. The SI unit of a couple moment is the Newton-meter (N-m).
A typical example to understand this concept is tightening a bolt with a lug wrench. A...
998
Work of a Couple Moment01:12

Work of a Couple Moment

1.1K
Mechanical engineering involves the study of motion, energy, and force, and is concerned with designing, manufacturing, and maintaining mechanical systems. One important concept in this field is the couple moment, produced by two equal and opposite forces acting at two points in a rigid body separated by a certain distance.
When the rigid body undergoes a differential displacement due to a couple, its motion can be divided into two parts: equal translation of the two points to their final...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Reconstruction of Ultrafine MnS-Induced Vacancy-Rich Co<sub>9</sub>S<sub>6.29</sub> Precatalysts in Mesoporous S-Doped N-Rich Hollow Carbon Nanotubes Enables Dynamic O-Vacancy Cycling for High-Performance Zn-Air Batteries.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Prediction of delirium in trauma patients using interpretable machine learning.

Scientific reports·2026
Same author

Palm sEMG-based user identification during doorknob rotation using a convolutional neural network.

Scientific reports·2026
Same author

Quantification of thyroid nodules in multiple ultrasonography systems.

Medical image analysis·2026
Same author

Age-stratified analysis of descending aorta diameter in traumatic massive hemorrhage: a machine learning approach.

Trauma surgery & acute care open·2026
Same author

Structure Dependent Accessibility of Active Sites Governs Catalytic Activity and Stability of Iridium Oxides in the Acidic Oxygen Evolution Reaction.

Journal of the American Chemical Society·2025
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: Jan 31, 2026

Behavioral Tasks for Examining Identity Recognition In Mice
06:58

Behavioral Tasks for Examining Identity Recognition In Mice

Published on: February 7, 2025

1.2K

Face Recognition in SSPP Problem Using Face Relighting Based on Coupled Bilinear Model.

Sang-Il Choi1, Yonggeol Lee2, Minsik Lee3

  • 1Department of Computer Science and Engineering, Dankook University, 126, Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do 448-701, Korea. choisi@dankook.ac.kr.

Sensors (Basel, Switzerland)
|December 26, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a coupled bilinear model to solve the single sample per person (SSPP) problem in face recognition. The model generates virtual images with varied illuminations from a single input image, improving recognition accuracy.

Keywords:
coupled bilinear modelface relightingsingle sample per person problem

More Related Videos

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.3K
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

1.6K

Related Experiment Videos

Last Updated: Jan 31, 2026

Behavioral Tasks for Examining Identity Recognition In Mice
06:58

Behavioral Tasks for Examining Identity Recognition In Mice

Published on: February 7, 2025

1.2K
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.3K
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

1.6K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Biometrics

Background:

  • Face recognition algorithms have reached peak performance in ideal conditions.
  • The single sample per person (SSPP) problem, where only one image per individual is available for training, remains a significant challenge.
  • Solving the SSPP problem is crucial for practical applications with limited image data.

Purpose of the Study:

  • To propose an efficient coupled bilinear model for generating virtual face images under varying illuminations.
  • To address the limitations of existing face recognition methods when dealing with the SSPP problem.
  • To enhance the training of feature spaces for improved face recognition with scarce data.

Main Methods:

  • Developed an efficient coupled bilinear model leveraging illuminance and texture information from a single input image.
  • The model retrieves illuminance information, which is correlated with the image, and combines it with the input image to estimate texture.
  • Generated numerous virtual images with diverse illumination conditions from the single input image.

Main Results:

  • The proposed method successfully generates high-quality virtual face images with varied illuminations.
  • These generated images effectively augment training data for the SSPP problem.
  • Experimental results demonstrate superior performance compared to existing face recognition algorithms for SSPP.

Conclusions:

  • The coupled bilinear model offers an effective solution for the single sample per person (SSPP) face recognition challenge.
  • The ability to generate virtual illumination conditions significantly improves the robustness of face recognition systems with limited training samples.
  • This approach provides a practical and efficient method for enhancing face recognition in real-world scenarios.