Jove
Visualize
Contact Us

Related Concept Videos

Association Areas of the Cortex01:21

Association Areas of the Cortex

6.0K
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,...
6.0K
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

6.8K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
6.8K
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

199
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
199
Force Classification01:22

Force Classification

1.4K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.4K
Prosopagnosia01:24

Prosopagnosia

237
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...
237
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

You might also read

Related Articles

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

Sort by
Same author

Multimodal medical image fusion using adaptive co-occurrence filter-based decomposition optimization model.

Bioinformatics (Oxford, England)·2021
Same author

Multi-Modal Medical Image Fusion Based on FusionNet in YIQ Color Space.

Entropy (Basel, Switzerland)·2020
Same journal

Retraction Note: An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis.

Multimedia tools and applications·2026
Same journal

Retraction Note: Covid-19 classification using sigmoid based hyper-parameter modified DNN for CT scans and chest X-rays.

Multimedia tools and applications·2026
Same journal

Retraction Note: Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing.

Multimedia tools and applications·2026
Same journal

Retraction Note: Modeling and prediction of KSE - 100 index closing based on news sentiments: an applications of machine learning model and ARMA (p, q) model.

Multimedia tools and applications·2026
Same journal

Retraction Note: COVID-19 Detection using adopted convolutional neural networks and high-performance computing.

Multimedia tools and applications·2026
Same journal

Human-like scene graph generation and evaluation.

Multimedia tools and applications·2026
See all related articles
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 Video

Updated: Aug 29, 2025

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

683

Wide aspect ratio matching for robust face detection.

Shi Luo1,2, Xiongfei Li1,2, Xiaoli Zhang1,2

  • 1Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012 China.

Multimedia Tools and Applications
|September 12, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a Wide Aspect Ratio Matching (WARM) strategy to improve face detection by sampling more positive anchors from extreme aspect ratio faces. This enhances model robustness and accuracy for challenging facial detection scenarios.

Keywords:
Anchor matchingConvolutional neural networkDeep learningFace detectionFeature enhancement

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.0K
Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.9K

Related Experiment Videos

Last Updated: Aug 29, 2025

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

683
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.0K
Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.9K

Area of Science:

  • Computer Vision
  • Machine Learning

Background:

  • Anchor-based methods are standard in face detection but struggle with extreme aspect ratio faces due to sampling failures.
  • Current methods often fail to capture faces with unusual aspect ratios, limiting detection model robustness.

Purpose of the Study:

  • To improve face detection performance by extending the sampling range of face aspect ratios.
  • To address the limitations of existing anchor matching strategies for extreme aspect ratio faces.

Main Methods:

  • Theoretical exploration of factors influencing maximum Intersection over Union (IoU) for faces.
  • Anchor matching simulations to evaluate aspect ratio sampling ranges.
  • Proposal of a Wide Aspect Ratio Matching (WARM) strategy for collecting diverse positive anchors.
  • Introduction of a Receptive Field Diversity (RFD) module for feature enhancement.

Main Results:

  • The WARM strategy effectively collects more representative positive anchors across a wide range of aspect ratios.
  • The RFD module provides diverse receptive fields, aiding in the capture of varied aspect ratios.
  • Achieved promising Average Precisions (APs) on the WIDER FACE dataset: 0.965 (easy), 0.955 (medium), and 0.904 (hard).
  • Demonstrated impressive generalization capability on the FDDB dataset.

Conclusions:

  • The proposed WARM strategy and RFD module significantly enhance the ability of face detectors to capture extreme aspect ratio faces.
  • The method offers a robust solution for improving face detection accuracy, particularly for challenging facial geometries.