Automatic Human Face Detection and Recognition Based On Facial Features Using Deep Learning Approach

Main Article Content

Rashmi Jatain
Manisha Jailia

Abstract

In recent years, there has been an increased emphasis placed on the identification of face traits in studies. The human face is the most significant characteristic that may be used in the process of identifying a person. Even the most genetically identical twins may be distinguished from one another by a few key facial characteristics. Therefore, to discern one from the other, a human face identification and detection system that is based on facial traits is necessary. This study suggests a technique for automated human face identification and recognition based on facial characteristics that are achieved via the use of deep learning. It would seem that deep learning, with its high rate of accuracy, would be an appropriate method to use while carrying out face recognition. Face detection and identification may be accomplished using a process known as deep learning. According to the results of the study, it is possible to conclude that the approach that was suggested is superior to other ways in terms of accuracy, precision, recall, and f1-score.

Article Details

How to Cite
Jatain, R. ., & Jailia, M. . (2023). Automatic Human Face Detection and Recognition Based On Facial Features Using Deep Learning Approach. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2s), 268–277. https://doi.org/10.17762/ijritcc.v11i2s.6146
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Articles

References

"cookbook.fortinet.com," 10 10 2018. [Online]. Available: https://cookbook.fortinet.com/face-recognition-configuration-in-forticentral/. [Accessed 10 10 2018].

Sutabri, Tata, Ade Kurniawan Pamungkur, and Raymond Erz Saragih. "Automatic attendance system for university student using face recognition based on deep learning." International Journal of Machine Learning and Computing 9.5 (2019): 668-674.

Azhaguraj, R., P. Arjun Kumar, S. Kadalarasan, K. Karthick, and G. Shunmugalakshmi. "Smart Attendance Marking System using Face Recognition." In 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), pp. 1784-1789. IEEE, 2022.

Lukas, Samuel, Aditya Rama Mitra, Ririn Ikana Desanti, and Dion Krisnadi. "Student attendance system in classroom using face recognition technique." In 2016 International Conference on Information and Communication Technology Convergence (ICTC), pp. 1032-1035. IEEE, 2016.

Teoh, K. H., et al. "Face recognition and identification using deep learning approach." Journal of Physics: Conference Series. Vol. 1755. No. 1. IOP Publishing, 2021.

Z. Yu, C. Zhang. “Image based Static Facial Expression Recognition with Multiple Deep Network Learning,” Acm on International Conference on Multimodal Interaction, Seattle, 2015, pp. 435-442.

Sutabri, Tata, Ade Kurniawan Pamungkur, and Raymond Erz Saragih. "Automatic attendance system for university student using face recognition based on deep learning." International Journal of Machine Learning and Computing 9.5 (2019): 668-674.

Qu, Danyang, et al. "An automatic system for smile recognition based on CNN and face detection." 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2018.

Lu, Peng, Baoye Song, and Lin Xu. "Human face recognition based on convolutional neural network and augmented dataset." Systems Science & Control Engineering 9.sup2 (2021): 29-37.

Hussain, Shaik Asif, and Ahlam Salim Abdallah Al Balushi. "A real time face emotion classification and recognition using deep learning model." Journal of physics: Conference series. Vol. 1432. No. 1. IOP Publishing, 2020.

Ullah, Rehmat, et al. "A real-time framework for human face detection and recognition in cctv images." Mathematical Problems in Engineering 2022 (2022).

Yan, Kewen, et al. "Face recognition based on convolution neural network." 2017 36th Chinese Control Conference (CCC). IEEE, 2017.

Stanko I. The Architectures of Geoffrey Hinton. In: Skansi S. (eds) Guide to Deep Learning Basics. Springer, Cham, 2020.

C. Edwards, “Deep learning hunts for signals among the noise,” Commun. ACM, vol. 61, no. 6, pp. 13–14, 2018.

G. Thomson, “Facial Recognition,” Encyclopedia, 2005. [Online]. Available: https://www.encyclopedia.com/science/encyclopedias-almanacs-transcripts-and-maps/facialrecognition. [Accessed: 11-Oct-2018].

M. Anggo and La Arapu, “Face Recognition Using Fisherface Method,” J. Phys. Conf. Ser., vol. 1028, no. 1, 2018.

Rajamanogaran, Murugan, S. Subha, S. Baghavathi Priya, and Jeevitha Sivasamy. "Contactless attendance management system using artificial intelligence." In Journal of Physics: Conference Series, vol. 1714, no. 1, p. 012006. IOP Publishing, 2021.