Deep Learning Convolutional Neural Network for Face Recognition:
A Review
Author (s)
Rondik J. Hassan & Adnan Mohsin Abdulazeez
Abstract
Face recognition is increasingly being used for solving various social-problems such as personal protection and authentication. As with other widely used biometric applications, facial recognition is a biometric instrument such as iris recognition, vein pattern recognition, and fingerprint recognition. Facial recognition identifies a person based on certain aspects of his physiology. Deep Learning (DL) is a branch of machine learning (ML) that can be used in image processing and pattern recognition to solve multiple problems, one of the applications is face recognition. With the advancement of deep learning, Convolution Neural Network (CNN) based facial recognition technology has been the dominant approach adopted in the field of face recognition. The purpose of this paper is to provide a review of face recognition approaches. Furthermore, the details of each paper, such as used datasets, algorithms, architecture, and achieved results are summarized and analyzed comprehensively.
Keywords: Face Recognition, Machine Learning, Deep Learning, Convolution Neural Network, Feature Extraction, Feature Matching.
| Title: | Deep Learning Convolutional Neural Network for Face Recognition: A Review |
|---|---|
| Author: | Rondik J. Hassan & Adnan Mohsin Abdulazeez |
| Journal Name: | International Journal of Science and Business |
| Website: | ijsab.com |
| ISSN: | ISSN 2520-4750 (Online), ISSN 2521-3040 (Print) |
| DOI: | https://doi.org/10.5281/zenodo.4471013 |
| Media: | Online |
| Volume: | 5 |
| Issue: | 2 |
| Acceptance Date: | 24/01/2021 |
| Date of Publication: | 27/01/2021 |
| PDF URL: | https://ijsab.com/wp-content/uploads/675.pdf |
| Free download: | Available |
| Page: | 114-127 |
| First Page: | 114 |
| Last Page: | 127 |
| Paper Type: | Literature Review |
| Current Status: | Published |
Cite This Article:
Rondik J. Hassan & Adnan Mohsin Abdulazeez (2021). Deep Learning Convolutional Neural Network for Face Recognition: A Review, International Journal of Science and Business, 5(2), 114-127. doi: https://doi.org/ 10.5281/zenodo.4471013
Retrieved from https://ijsab.com/wp-content/uploads/675.pdf
About Author (s)
Rondik J.Hassan (corresponding author), Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: rondik.jamaluddin@gmail.com
Professor Adnan Mohsin Abdulazeez, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: adnan.mohsin@dpu.edu.krd