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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

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Deep Learning Models for Multiple Face Mask Detection under a Complex Big Data Environment.

V Rekha¹, J Samuel Manoharan², R Hemalatha¹

¹Assistant Professor, Dept. of Computer Science, Rajalakshmi Engineering College, Thandalam, Chennai.

Procedia Computer Science

|January 9, 2023

Summary

This summary is machine-generated.

This study explores deep learning models for effective face mask detection in crowded environments, crucial for managing the Covid-19 pandemic. These advanced models address big data challenges where traditional methods fall short.

Keywords:

Big Data Complex Data analytics Deep Learning models Face Mask Detection Multi – Sensor Data Acquisition

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Area of Science:

Computer Science
Artificial Intelligence
Public Health

Background:

The Covid-19 pandemic necessitates effective public health measures, including widespread face mask usage.
Manual monitoring of face mask compliance is labor-intensive and inefficient.
Automated face mask detection systems are needed, especially in large-scale, data-intensive scenarios.

Purpose of the Study:

To investigate deep learning models for detecting multiple face masks in crowded settings.
To address the challenges posed by big data in real-time monitoring applications.
To propose solutions beyond traditional face detection methods for pandemic control.

Main Methods:

Utilizing deep learning architectures suitable for big data processing.
Evaluating model performance in detecting multiple individuals with face masks in complex environments.
Focusing on models capable of handling high volumes of sensor data.

Main Results:

Deep learning models demonstrate efficacy in detecting multiple face masks within crowded environments.
The proposed models are well-suited for big data scenarios, outperforming standalone detection methods.
Successful implementation in scenarios with large incoming data streams.

Conclusions:

Deep learning offers a robust solution for automated face mask detection in public health crises.
The study highlights the necessity of advanced AI for managing big data in surveillance.
Effective face mask detection systems are vital for controlling viral transmission.