Open Access
Issue |
ITM Web Conf.
Volume 40, 2021
International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|
|
---|---|---|
Article Number | 03047 | |
Number of page(s) | 6 | |
Section | Computing | |
DOI | https://doi.org/10.1051/itmconf/20214003047 | |
Published online | 09 August 2021 |
- Amit D. Ranjit K. Vijay B. Gender Recognition Through Face Using Deep Learning.Procedia Computer Science 132 (2018) 2–10 [CrossRef] [Google Scholar]
- Sajid Ali Khan, Muhammad Nazir, Naveed Riaz(2013)”Gender Classification using Multi-Level Wavelets on Real World Face Images”, Springer Acta Polytechnica Hungarica Vol. 10, No. 4. [Google Scholar]
- S. Baluja and H. A. Rowley. Boosting sex identification performance. Int. J. Comput. Vision, 71(1):111–119, 2007. [CrossRef] [Google Scholar]
- Jridi, M. Napoléon, T. Alfalou, A. One lens optical correlation: Application to face recognition. Appl. Opt. 2018. [Google Scholar]
- Tivive FHC, A.Bouzerdoum(Sep 2016) ”A gender recognition system using shunting inhibitory convolutional neural networks” In: International Joint Conference on Neural Networks; Vancouver, Canada. New York, NY, USA: IEEE. [Google Scholar]
- Vaishnavi Y. Mali. Human Gender Classification using Machine Learning. y (IJERT) Vol. 8 Issue 12, December-2019 [Google Scholar]
- Ma, Z. Ding, Y. Li, B. Yuan, X. Deep CNNs with Robust LBP Guiding Pooling for Face Recognition. Sensors 2018. [Google Scholar]
- Van de Wolfshaar, J. Karaaba, M.F. Wiering, M.A. Deep convolutional neural networks and support vector machines for gender recognition. In Proceedings of the 2015 IEEE Symposium Series on Computational Intelligence, Cape Town, South Africa, 7–10 December 2015. [Google Scholar]
- Duan, M. Li, K. Yang, C. Li, K. A hybrid deep learning CNN–ELM for age and gender classification Neurocomputing 2018. [Google Scholar]
- Levi G., Hassner T. Age and gender classification using convolutional neural networks. Boston, MA, USA, 7–12 June 2015. [Google Scholar]
- Rajeev, R. Vishal, M.P. Rama, C. HyperFace. A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition. IEEE Trans. Pattern. Anal. Mach. Intell. 2019 [Google Scholar]
- Yassin Kortli, Maher Jridi, Ayman Al Falou and Mohamed Atri. Face Recognition Systems: A Survey. Sensors January 2020 [Google Scholar]
- Khalil Khan, Muhammad Attique, Ikram Syed and Asma Gul. Automatic Gender Classification through Face Segmentation. Symmetry 2019 [Google Scholar]
- Alessandra Lumini, Loris Nanni, and Sheryl Brahnam. 2016. Ensemble of texture descriptors and classifiers for face recognition. Appl. Comput. Info. (2016). [Google Scholar]
- Shubham Patil Bhagyashree Patil, Ganesh Tatkare.Gender Recognition and Age Approximation using Deep Learning Techniques.y (IJERT) Vol. 9 Issue 04, April-2020 [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.