Search research articles

Related Concept Videos

Masking and Demasking Agents

Masking and Demasking Agents

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...

You might also read

Related Articles

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

Sort by

Same author

Exploring the antibacterial potential of a designed peptide against Gardnerella vaginalis.

Molecular biology reports·2026

Same author

Oral health status of NCC cadets in Uttar Pradesh: A cross-sectional study.

Bioinformation·2026

Same author

Draft genome sequence of <i>Rhodococcus erythropolis</i> DR10, a potential oil degradation actinobacteria.

Microbiology resource announcements·2026

Same author

Assessment of Hippocampal, Prefrontal Cortical, and Striatal Dopaminergic Circuitry Underlying Altered Social Behavior in Diabetes.

Molecular neurobiology·2026

Same author

Impact of School-Based Periodontal Health Education Programs on Gingival Health in Adolescents: A Cluster-Randomized Controlled Trial.

Journal of pharmacy & bioallied sciences·2026

Same author

Efficient production of ectoine using isolated Halomonas smyrnensis IIIM VA-6 at the reduced salinity approach.

FEMS microbiology letters·2026

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

Search research articles

Related Experiment Video

Updated: Sep 30, 2025

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

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

Published on: December 15, 2023

A novel algorithm for mask detection and recognizing actions of human.

Puja Gupta¹, Varsha Sharma¹, Sunita Varma²

¹School of Information Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh 462033 India.

Expert Systems with Applications

|March 14, 2022

Summary

This study introduces an enhanced Mask R-CNN for real-time face recognition with masks, crucial for Covid-19 safety. The system accurately detects masked individuals and identifies anomalies in video surveillance, outperforming existing methods.

Keywords:

Apache MXNet Image detection Mask R-CNN Resnet-152 Video surveillance

More Related Videos

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Related Experiment Videos

Last Updated: Sep 30, 2025

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

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

Published on: December 15, 2023

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Area of Science:

Computer Science
Artificial Intelligence
Biometrics

Background:

Face recognition is challenged by widespread mask usage due to Covid-19.
Real-time processing is essential for anomaly detection in video surveillance.
Conventional methods struggle with computationally expensive features and early activity classification.

Purpose of the Study:

To develop an effective face recognition system for individuals wearing masks.
To enable real-time anomaly detection in video surveillance under unconstrained conditions.
To improve the accuracy and efficiency of detecting masked individuals and unusual activities.

Main Methods:

An expanded Mask R-CNN (Ex-Mask R-CNN) architecture is proposed.
Convolutional Neural Network (CNN)-based features are utilized for robust recognition.
A two-step process involves mask detection and Multi-CNN based anomaly forecasting.

Main Results:

The Ex-Mask R-CNN achieves high accuracy in recognizing faces with masks.
The system successfully performs real-time anomaly detection.
Experimental results demonstrate superior performance compared to state-of-the-art anomaly detection systems.

Conclusions:

The proposed Ex-Mask R-CNN effectively addresses the challenges of face recognition with masks.
The approach maintains real-time efficiency crucial for practical video surveillance applications.
This method enhances security by accurately identifying masked individuals and detecting anomalies.