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All issues Volume 616 (2025) E3S Web Conf., 616 (2025) 02013 References
Open Access
Issue
E3S Web Conf.
Volume 616, 2025
2nd International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2025)
Article Number 02013
Number of page(s) 8
Section Green Computing
DOI https://doi.org/10.1051/e3sconf/202561602013
Published online 24 February 2025
  1. A. Soetan, L. Zhang, Mitigating Infectious Disease Transmission with Face Mask Detection Using Machine Learning, in 2023 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) (IEEE, 2023), pp. 423–427 [CrossRef] [Google Scholar]
  2. C. Sudthongkhong, B. Intarapasan, T. Wongsheree, K. Thanasuan, B. Pattanapipat, P. Suksai, Real-Time Face Mask Detection with Deep Learning for Pandemic Safety, in 2023 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (IEEE, 2023), pp. 213–217 [Google Scholar]
  3. A. Kanavos, O. Papadimitriou, K. Al-Hussaeni, M. Maragoudakis, I. Karamitsos Realtime detection of face mask usage using convolutional neural networks, Computers 13, 182 (2024). [CrossRef] [Google Scholar]
  4. J. Yedukondalu, T.Y. Singh, D. Sharma, R.S. Singh, L.D. Sharma, Face Mask Detection Using Image Processing and Convolutional Neural Networks, in 2022 IEEE 6th Conference on Information and Communication Technology (CICT) (IEEE, 2022), pp. 1–4 [Google Scholar]
  5. P. Singh, R. Kumar Real-time mask detection using cnns with tensorflow and opencv, International Journal of Computer Vision and Machine Learning 15, 121 (2023). 10.1016/j.cvim.2023.08.007 [Google Scholar]
  6. P.G. Nair Edge device integration for mask detection using opencv and tensorflow, Journal of AI and Internet of Things 10, 345 (2023). 10.1007/s00192-023-01999-0 [Google Scholar]
  7. D. Lorenzo Face mask detection using haar cascade and svm, https://github.com/davidlorenzo47/facemask (2023), accessed: 2023-11-05 [Google Scholar]
  8. I.C. on Face Mask Detection, Face Mask Detection Using CNN Model and Transfer Learning, in IEEE Xplore (2023), accessed: 2024-11-05, https://ieeexplore.ieee.org/document/10351205 [Google Scholar]
  9. M. Wang, H. Sun, J. Shi, X. Liu, X. Cao, L. Zhang, B. Zhang, Q-YOLO: Efficient inference for real-time object detection, in Asian Conference on Pattern Recognition (Springer, 2023), pp. 307–321 [Google Scholar]
  10. G. Kaur, R. Sinha, P.K. Tiwari, S.K. Yadav, P. Pandey, R. Raj, A. Vashisth, M. Rakhra Face mask recognition system using cnn model, Neuroscience Informatics 2, 100035 (2022). [CrossRef] [Google Scholar]
  11. A. Sarraf, M. Azhdari, S. Sarraf et al. A comprehensive review of deep learning architectures for computer vision applications, American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) 77, 1 (2021). [Google Scholar]
  12. H. Huang, C. Wang, B. Dong Nostalgic adam: Weighting more of the past gradients when designing the adaptive learning rate, arXiv preprint arXiv:1805.07557 (2018). [Google Scholar]
  13. A. Nowrin, S. Afroz, M.S. Rahman, I. Mahmud, Y.Z. Cho Comprehensive review on facemask detection techniques in the context of covid-19, IEEE access 9, 106839 (2021). [CrossRef] [Google Scholar]
  14. M.A. Ai, A. Shanmugam, S. Muthusamy, C. Viswanathan, H. Panchal, M. Krishnamoorthy, D.S.A. Elminaam, R. Orban Real-time facemask detection for preventing covid-19 spread using transfer learning based deep neural network, Electronics 11, 2250 (2022). [CrossRef] [Google Scholar]
  15. R. Shanmugamani, Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras (Packt Publishing Ltd, 2018) [Google Scholar]
  16. T. Carneiro, R.V.M. Da Nóbrega, T. Nepomuceno, G.B. Bian, V.H.C. De Albuquerque, P.P. Reboucas Filho Performance analysis of google colaboratory as a tool for accelerating deep learning applications, Ieee Access 6, 61677 (2018). [CrossRef] [Google Scholar]
  17. I.S.A. MAKBOUL, Ph.D. thesis, Université Ibn Khaldoun-Tiaret (2020) [Google Scholar]

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