EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 391 (2023) E3S Web Conf., 391 (2023) 01087 References
Open Access
Issue
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
Article Number 01087
Number of page(s) 9
DOI https://doi.org/10.1051/e3sconf/202339101087
Published online 05 June 2023
  1. Ahonen, T., Hadid, A., & Pietikainen, M. (2004). Face recognition with local binary patterns. In Proceedings of the European Conference on Computer Vision (pp. 469–481). [Google Scholar]
  2. Chen, Y., Lai, Z., & Chen, H. (2020). Smart door security system based on face recognition and IoT technology. IEEE Access, 8, 85608–85619. [Google Scholar]
  3. Shan, S., Gong, S., & McOwan, P.W. (2005). Facial expression recognition based on local binary patterns: a comprehensive study. Image and Vision Computing, 23(9), 913–929. [Google Scholar]
  4. Turan, A., & Barshan, E. (2015). Face recognition with local binary patterns-based histograms of oriented gradients. IET Biometrics, 4(4), 245–253. [Google Scholar]
  5. Zhang, Z., Yan, J., & Liu, B. (2017). Face recognition using deep learning: A survey. Frontiers of Computer Science, 11(4), 478–490. [Google Scholar]
  6. Huang, D., Shan, C., Ardabilian, M., & Chen, L. (2011). Local binary patterns and its variants for face recognition: A comprehensive review. International Journal of Computer Vision, 91(1), 68–90. [Google Scholar]
  7. Zhang, W., & Shan, S. (2010). Local Gabor binary pattern histogram sequence (LGBPHS): A novel non-statistical model for face representation and recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1794–1801). [Google Scholar]
  8. Yang, Y., & Ai, H. (2019). A survey on face recognition technology. Journal of Ambient Intelligence and Humanized Computing, 10(4), 1321–1338. [Google Scholar]
  9. Liu, C., Luo, L., Yin, X., & Wang, Q. (2020). A smart access control system based on facial recognition and deep learning. Sensors, 20(13), 3598. [CrossRef] [PubMed] [Google Scholar]
  10. Kalka, N.D., & Raskar, S.N. (2021). Security door access using Raspberry Pi and facial recognition. In Proceedings of the IEEE International Conference on Emerging Trends in Information Technology and Engineering (pp. 183–187). [Google Scholar]
  11. Gonzalez-Serrano, J., Cabello, E., Ortega, J., & Fernandez-Breis, J.T. (2019). Biometric recognition using a Raspberry Pi-based system [Google Scholar]
  12. Navneet Dalal, Bill Triggs. Histograms of Oriented Gradients for Human Detection. International Conference on Computer Vision & Pattern Recognition (CVPR ’05), Jun 2005, San Diego, United States. pp. 886–893, ff10.1109/CVPR.2005.177ff. ffinria-00548512f [Google Scholar]
  13. Vahid Kazemi; Josephine Sullivan. One millisecond face alignment with an ensemble of regression trees, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 23-28 June 2014. [Google Scholar]
  14. Fischler, M.A. and R.A. Elschlager, 1973. The representation and matching of pictorial structures. IEEE Transactions on Computers, 22(1): 67–92. [CrossRef] [Google Scholar]
  15. Sirovich, L. and M. Kirby, 1987. Low-dimensional procedure for the characterization of human faces. JOSA A, 4(3): 519–524 [CrossRef] [Google Scholar]
  16. Matthew A. Turk, and Alex P. Pentland, “Face Recognition Using Eigenfaces”, Massachusetts Institute of Technology. [Google Scholar]
  17. Kanchan S, Gorgede and Ankita Baoney, “A Novel Codebook Technique for 3D Face Recognition”, International Journal of Innovative Research in Computer and Communication Engineering, June 2016. [Google Scholar]
  18. Paul Viola., Michael Jones. “Robust Real-Time Object Detection”. Citeseerx.ist.psu.edu. N.P., 2017. Web. 6 Apr. 2017. [Google Scholar]
  19. Vijay, T., Rohit Phadatare, Sujeet Kumar and Nitesh Patel, “Real Time Face Detection, Recognition and Tracking System for Human Activity Tracking”, in ternational Journal of Innovative Research in Computer and Communication Engineering,(3), March 2016. [Google Scholar]
  20. Emgu, C.V.: Open, C.V. in .NET: http://www.emgu.com/wiki/index.php/Main_Page Access on 13-08-2017 [9] Jigar M. Pandya, DevangRathod, Jigna and J. Jadav “A Survey of Face Recognition approach”, in ternational Journal of Engineering Research and Applications (IJERA), (1), 2013, pp. 632–635. [Google Scholar]
  21. Tharanga JGR, Samara Koon SMSC, Karunarathne TAP, Liyanage KLPM, Gamage MPAW, et al. (2013) Smart attendance using real-time face recognition (SMART-FR). Department of Electronic and Computer Engineering, Sri LankaInstitute of Information Technology (SLIIT), Malabe, Sri Lanka. [Google Scholar]
  22. Ion Marques and Manuel Grana, “Face Recognition Algorithms”, Universidad del Pais Vasco Basque Country University, June 16, 2010. [Google Scholar]
  23. Nicolas Morizet, Frdric Amiel, Insaf Dris Hamed, Thomas Ea A Comparative Implementation of PCA Face Recognition Algorithm, ICECS’07. [Google Scholar]
  24. S.B. Thorat Dr., “Facial recognition technology: an analysis with scope in India”, (ijcsis) international journal of computer science and information security, vol. 8, no. 1, 2010 [Google Scholar]
  25. Y. Jeevan Nagendra Kumar, T.V. Rajini Kanth Dr., “GIS-MAP Based Spatial Analysis of Rainfall Data of Andhra Pradesh and Telangana States Using R”, in Ternational Journal of Electrical and Computer Engineering (IJECE), Vol 7, No 1, February 2017, Scopus Indexed Journal, ISSN: 2088-8708 [Google Scholar]
  26. B Sankara Babu, A Suneetha, G. Charles Babu, Y. Jeevan Nagendra Kumar, G. Karuna, “Medical Disease Prediction using Grey Wolf optimization and Auto Encoder based Recurrent Neural Network” Periodicals of Engineering and Natural Sciences, Vol 6 Issue 1 Pg: 229–240 ISSN 2303-4521 Jun 2018 [CrossRef] [Google Scholar]
  27. Y. Jeevan Nagendra Kumar Dr., Guntreddi Sai Kiran, Partapu Preetham, Chila Lohith, Guntha Sai Roshik, G. Vijendar Reddy, “A Data Science View on Effects of Agriculture & Industry Sector on the GDP of India” in Ternational Journal of Recent Technology and Engineering, Volume-8, Issue-1, May 2019, ISBN: 2277-3878. [Google Scholar]
  28. Y. Jeevan Nagendra Kumar Dr., Guntreddi Sai Kiran, Partapu Preetham, Chila Lohith, Guntha Sai Roshik, G. Vijendar Reddy, “A Data Science View on Effects of Agriculture & Industry Sector on the GDP of India” in ternational Journal of Recent Technology and Engineering, Volume-8, Issue-1, May 2019, ISSN: 2277-3878 [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.