Face Recognition and Identification using Deep Learning Approach. Issue 1 (February 2021)
- Record Type:
- Journal Article
- Title:
- Face Recognition and Identification using Deep Learning Approach. Issue 1 (February 2021)
- Main Title:
- Face Recognition and Identification using Deep Learning Approach
- Authors:
- Teoh, KH
Ismail, RC
Naziri, SZM
Hussin, R
Isa, MNM
Basir, MSSM - Abstract:
- Abstract: Human face is the significant characteristic to identify a person. Everyone has their own unique face even for twins. Thus, a face recognition and identification are required to distinguish each other. A face recognition system is the verification system to find a person's identity through biometric method. Face recognition has become a popular method nowadays in many applications such as phone unlock system, criminal identification and even home security system. This system is more secure as it does not need any dependencies such as key and card but only facial image is needed. Generally, human recognition system involves 2 phases which are face detection and face identification. This paper describes the concept on how to design and develop a face recognition system through deep learning using OpenCV in python. Deep learning is an approach to perform the face recognition and seems to be an adequate method to carry out face recognition due to its high accuracy. Experimental results are provided to demonstrate the accuracy of the proposed face recognition system.
- Is Part Of:
- Journal of physics. Volume 1755:Issue 1(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1755:Issue 1(2021)
- Issue Display:
- Volume 1755, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1755
- Issue:
- 1
- Issue Sort Value:
- 2021-1755-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1755/1/012006 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25217.xml