research-article

Unmasking Compliance: Leveraging Machine Learning for RealTimeFace Mask Detection and Public Safety

Authors:

Divya Gupta,

Sanchit Wadehra,

Jaspreet Kaur,

Sai Viswanath SharmaAuthors Info & Claims

ICIMMI '23: Proceedings of the 5th International Conference on Information Management & Machine Intelligence

Article No.: 38, Pages 1 - 4

https://doi.org/10.1145/3647444.3647864

Published: 13 May 2024 Publication History

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Abstract

During the COVID-19 pandemic, face masks have become a crucial part of maintaining public health. The real-time face mask detector has potential implications for public health and safety by allowing for quick and efficient monitoring of mask-wearing compliance in public spaces. The integration of machine learning with a web-based solution can make it easier to deploy in real-world scenarios. In this research paper, we present a real-time face mask detector that is developed using machine learning with ml5.js, a web-based machine learning library, making it easily applicable in real-world situations. The detector can accurately identify individuals not wearing masks in real-world scenarios, with an average accuracy of 78.51% .This research provides a promising approach to address the need for mask-wearing compliance and public safety.

References

[1]

Hiten Goyal, KaranveerSidana, Charanjeet Singh, Abhilasha Jain, and Swati Jindal. 2022. A real time face mask detection system using convolutional neural network. Multimedia Tools and Applications 81, 11 (2022), 14999–15015.

Digital Library

Google Scholar

[2]

M Hemasri, S Jesintha Singh Ranjith, M Sacratees, M Vidhyasagar, and N Shimmar Rahim. 2021. Real Time Object Detection and Tracking Using Open cv. Annals of the Romanian Society for Cell Biology (2021), 8080–8091.

Google Scholar

[3]

Kalla Kiran, Bokka Vamsi Kiran, DevarapalliCheswanth Sai, Gaggala Vijay Vamsi, and Pitta Rani Salomi. 2021. Face mask detection using machine learning. Available at SSRN 3925736 (2021).

Google Scholar

[4]

B Anil Kumar and Mohan Bansal. 2023. Face mask detection on photo and real-time video images using Caffe-MobileNetV2 transfer learning. Applied Sciences 13, 2 (2023), 935.

Crossref

Google Scholar

[5]

PreetiNagrath, Rachna Jain, Agam Madan, Rohan Arora, Piyush Kataria, and Jude Hemanth. 2021. SSDMNV2: A real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2. Sustainable cities and society 66 (2021), 102692.

Google Scholar

[6]

Joseph Redmon and Ali Farhadi. 2018. Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767 (2018).

Google Scholar

[7]

Florian Schroff, Dmitry Kalenichenko, and James Philbin. 2015. Facenet: A unified embedding for face recognition and clustering. InProceedings of the IEEE conference on computer vision and pattern recognition. 815–823.

Crossref

Google Scholar

[8]

Yi Yang, Hengliang Luo, Huarong Xu, and Fuchao Wu. 2015. Towards real-time traffic sign detection and classification. IEEE Transactions onIntelligent transportation systems 17, 7 (2015), 2022–2031.

Digital Library

Google Scholar

[9]

Ji, S., Yang, M., Adelson, E. H., & Wu, Y. (2013). 3d convolutional neural networks for human action recognition. In Proceedings of the IEEE international conference on computer vision (pp. 2189-2196).

Google Scholar

[10]

Wang, L., Ouyang, W., Wang, X., & Hu, W. (2015). Visual object tracking with deep convolutional neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3184-3191).

Google Scholar

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Dubey PDubey PIwendi CBiamba CRao D(2025)Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach With Adaptive AlgorithmsIEEE Access10.1109/ACCESS.2025.353276413(17325-17339)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3532764

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ICIMMI '23: Proceedings of the 5th International Conference on Information Management & Machine Intelligence

November 2023

1215 pages

ISBN:9798400709418

DOI:10.1145/3647444

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Published: 13 May 2024

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ICIMMI 2023: International Conference on Information Management & Machine Intelligence

November 23 - 25, 2023

Jaipur, India

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Dubey PDubey PIwendi CBiamba CRao D(2025)Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach With Adaptive AlgorithmsIEEE Access10.1109/ACCESS.2025.353276413(17325-17339)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3532764

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Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy

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