EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 44 (2022) ITM Web Conf., 44 (2022) 03025 References
Open Access
Issue
ITM Web Conf.
Volume 44, 2022
International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
Article Number 03025
Number of page(s) 10
Section Computing
DOI https://doi.org/10.1051/itmconf/20224403025
Published online 05 May 2022
  1. M. A. Hoque, T. Islam, T. Ahmed and A. Amin, “Autonomous Face Detection System from Real-time Video Streaming for Ensuring the Intelligence Security System,” 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020, pp. 261–265, doi: 10.1109/ICACCS48705.2020.9074260. [CrossRef] [Google Scholar]
  2. P. Apoorva, H.C. Impana, S.L. Siri, M.R. Varshitha. and B. Ramesh, “Automated Criminal Identification by Face Recognition using Open Computer Vision Classifiers,” 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), 2019, pp. 775–778, doi: 10.1109/IC-CMC.2019.8819850. [CrossRef] [Google Scholar]
  3. M. Kushal, K.B.V. Kumar, C.M.J. Kumar and M. Pappa, “ID Card Detection with Facial Recognition using Tensorflow and OpenCV,” 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA), 2020, pp. 742–746, doi: 10.1109/ICIRCA48905.2020.9183342. [CrossRef] [Google Scholar]
  4. Ahmad, Faizan Najam, Aaima Ahmed, Zeeshan. (2013). Image-based Face Detection and Recognition: “State of the Art”. IJCSI International Journal of Computer Science Issues. 9. [Google Scholar]
  5. Hong Zhao, Xi-Jun Liang, Peng Yang, “Research on Face Recognition Based on Embedded System”, Mathematical Problems in Engineering, vol. 2013, Article ID 519074, 6 pages, 2013. [Google Scholar]
  6. E. O. Akay, K. O. Canbek and Y. Oniz, “Automated Student Attendance System Using Face Recognition,” 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2020, pp. 1–5, doi: 10.1109/ISM-SIT50672.2020.9255052. [Google Scholar]
  7. A. Ben Thabet and N. Ben Amor, “Enhanced smart doorbell system based on face recognition,” 2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2015, pp. 373–377, doi: 10.1109/STA.2015.7505106. [Google Scholar]
  8. Aashna, R. Bhatia Parallel Implementation of Face Detection Algorithm on GPU 2016 2nd International Conference on Next Generation Computing Technologies (NGCT-2016) Dehradun, India 14-16 October 2016. [Google Scholar]
  9. Neha Kumari Dubey, Pooja M.R., K. Vishal, Dhanush Gowda H.L., Keertiraj B.R., 2020, Face Recognition based Attendance System, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH TECHNOLOGY (IJERT) Volume 09, Issue 06 (June 2020). [Google Scholar]
  10. D. A. Chowdhry, A. Hussain, M. Z. Ur Rehman, F. Ahmad, A. Ahmad and M. Pervaiz, “Smart security system for sensitive area using face recognition,” 2013 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (CSUDET), 2013, pp. 11–14, doi: 10.1109/CSUDET.2013.6670976. [CrossRef] [Google Scholar]
  11. V. SureshDr., Facial Recognition Attendance System Using Python and OpenCv, Quest Journals, Journal of Software Engineering and Simulation Volume 5 Issue 2 (2019) pp. 18–29. [Google Scholar]
  12. S. Dev and T. Patnaik, “Student Attendance System using Face Recognition,” 2020 International Conference on Smart Electronics and Communication (ICOSEC), 2020, pp. 90–96, doi: 10.1109/ICOSEC49089.2020.9215441. [CrossRef] [Google Scholar]
  13. Khaled Md Hasan Human Face Detection Techniques: A Comprehensive Review and Future Research Directions. [Google Scholar]
  14. Hasan, M.K., Ahsan, M.S., Abdullah-Al-Mamun, Newaz, S.H., Lee, G.M. (2021). Human Face Detection Techniques: A Comprehensive Review and Future Research Directions. Electronics. [Google Scholar]
  15. Smitha, Pavithra S. Hegde, Afshin, 2020, Face Recognition based Attendance Management System, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH TECHNOLOGY (IJERT) Volume 09, Issue 05 (May 2020). [Google Scholar]
  16. Shivam Singh, Prof. S. Graceline Jasmine, 2019, Face Recognition System, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH TECHNOLOGY (IJERT) Volume 08, Issue 05 (May 2019). [Google Scholar]
  17. Owayjan, Michel Dergham, Amer Haber, Gerges Fakih, Nidal Hamoush, Ahmad Abdo, Elie. (2013). Face Recognition Security System. [Google Scholar]
  18. K. Goyal, K. Agarwal and R. Kumar, “Face detection and tracking: Using OpenCV,” 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), 2017, pp. 474–478, doi: 10.1109/ICECA.2017.8203730. [CrossRef] [Google Scholar]
  19. X. Han and Q. Du, “Research on face recognition based on deep learning,” 2018 Sixth International Conference on Digital Information, Networking, and Wireless Communications (DINWC), 2018, pp. 53–58, doi: 10.1109/DINWC.2018.8356995. [CrossRef] [Google Scholar]
  20. H. Zhang, Z. Qu, L. Yuan and G. Li, “A face recognition method based on LBP feature for CNN,” 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017, pp. 544–547, doi: 10.1109/IAEAC.2017.8054074. [CrossRef] [Google Scholar]
  21. Tejashree Dhawle et al., Face Detection and Recognition using OpenCV and Python, IRJET, vol 07, issue 10. [Google Scholar]
  22. Kadir, Kushsairy Kamaruddin, Mohd Nasir, Haidawati Safie, Sairul Bakti, Zulkifli. (2014). A comparative study between LBP and Haar-like features for Face Detection using OpenCV. 335–339. doi: 10.1109/ICE2T.2014.7006273. [Google Scholar]
  23. X. Peng, J. Ma, Y. Liu, J. He, W. Wang and Y. Wang, “Research on Face Recognition Based on Small Samples of CNN,” 2019 IEEE International Conference on Electron Devices and Solid-State Circuits (EDSSC), 2019, pp. 1–3, doi: 10.1109/EDSSC.2019.8754183. [Google Scholar]
  24. P. Laytner, C. Ling and Q. Xiao, “Robust face detection from still images,” 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM), 2014, pp. 76–80, doi: 10.1109/CIBIM.2014.7015446. [CrossRef] [Google Scholar]
  25. Lee, Hai-Wu Peng, Fan-Fan Lee, Xiu-Yun Dai, Hong-Nian Zhu, Ying. (2018). Research on face detection under different lighting. 1145–1148. doi: 10.1109/ICASI.2018.8394486. [Google Scholar]
  26. A. Nag, J. N. Nikhilendra and M. Kalmath, “IOT Based Door Access Control Using Face Recognition,” 2018 3rd International Conference for Convergence in Technology (I2CT), 2018, pp. 1–3, doi: 10.1109/I2CT.2018.8529749. [Google Scholar]
  27. Lal, Madan Kumar, Kamlesh Arain, Rafaqat Maitlo, Abdullah Ruk, Sadaquat Shaikh, Hi-Dayatullah. (2018). Study of Face Recognition Techniques: A Survey. International Journal of Advanced Computer Science and Applications. 9. doi: 10.14569/IJACSA.2018.090606. [Google Scholar]
  28. Irjanto, Nourman Surantha, Nico. (2020). Home Security System with Face Recognition based on Convolutional Neural Network. International Journal of Advanced Computer Science and Applications. 11. doi: 10.14569/IJACSA.2020.0111152. [Google Scholar]
  29. Gomes, Clyde Chanchal, Sagar Desai, Tanmay Jadhav, Dipti. (2020). Class Attendance Management System using Facial Recognition. ITM Web of Conferences. 32. 02001. doi: 10.1051/itmconf/20203202001. [CrossRef] [EDP Sciences] [Google Scholar]
  30. M. Srivastava, A. Kumar, A. Dixit and A. Kumar, “Real Time Attendance System Using Face Recognition Technique,” 2020 International Conference on Power Electronics IoT Applications in Renewable Energy and its Control (PARC), 2020, pp. 370–373, doi: 10.1109/PARC49193.2020.236628. [CrossRef] [Google Scholar]
  31. A. Singh, D. Gupta and N. Mittal, “Enhancing Home security systems Using IOT,” 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA), 2019, pp. 133–137, doi: 10.1109/ICECA.2019.8821833. [CrossRef] [Google Scholar]
  32. A. Singh, D. Gupta and N. Mittal, “Enhancing Home security systems Using IOT,” 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA), 2019, pp. 133–137, doi: 10.1109/ICECA.2019.8821833. [CrossRef] [Google Scholar]
  33. U. Waghmode, S. Tandale, “Real time Unat tended Object Identification”, International Conference on Computing, Communication, Control and Automation (ICCUBEA), 2017, doi: 10.1109/IC-CUBEA.2018.8477233. [Google Scholar]
  34. Zhukovyts’kyy, Ihor Pakhomova, Victoria Do-Manskay, Halyna Nechaiev, Andrew. (2019). Distribution of information flows in the advanced network of MPLS of railway transport by means of a neural model. MATEC Web of Conferences. 294. 04007. doi: 10.1051/matecconf/201929404007. [CrossRef] [EDP Sciences] [Google Scholar]
  35. Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey E. (2017-05-24). “ImageNet classification with deep convolutional neural networks” (PDF). Communications of the ACM. 60 (6): 84–90. doi: 10.1145/3065386 [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.