Results 51 to 60 of about 2,180,576 (223)

Training methods for facial image comparison: a literature review [PDF]

, 2011
This literature review was commissioned to explore the psychological literature relating to facial image comparison with a particular emphasis on whether individuals can be trained to improve performance on this task.
Hillstrom, Anne, Hope, Lorraine, Sauer, James   +2 more
core  

The Effects of AI-Driven Face Restoration on Forensic Face Recognition

Applied Sciences
In biometric recognition, face recognition is a mature and widely used technique that provides a fast, accurate, and reliable method for human identification.
Mengxuan Yang, Shengnan Li, Jinhua Zeng
doaj   +1 more source

Longitudinal Study of Child Face Recognition

, 2017
We present a longitudinal study of face recognition performance on Children Longitudinal Face (CLF) dataset containing 3,682 face images of 919 subjects, in the age group [2, 18] years. Each subject has at least four face images acquired over a time span
Deb, Debayan, Jain, Anil K., Nain, Neeta
core   +1 more source

Design and Implementation of an Online Social Network with Face Recognition

Journal of Advances in Information Technology, 2010
This paper presents the idea of an online social network that makes use of the face recognition technology. With the technology, friend relationship can be established without the need of having the text-based information of a user, friend recommendation
Ray K. C. Lai, Jack C. K. Tang, Angus K. Y. Wong, Philip I. S. Lei   +3 more
doaj   +1 more source

A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking

Applied Sciences
Masked face recognition (MFR) has emerged as a critical domain in biometric identification, especially with the global COVID-19 pandemic, which introduced widespread face masks.
Mohamed Mahmoud, Mahmoud SalahEldin Kasem, Hyun-Soo Kang   +2 more
doaj   +1 more source

Efficient Decision-based Black-box Adversarial Attacks on Face Recognition

, 2019
Face recognition has obtained remarkable progress in recent years due to the great improvement of deep convolutional neural networks (CNNs). However, deep CNNs are vulnerable to adversarial examples, which can cause fateful consequences in real-world ...
Dong, Yinpeng, Li, Zhifeng, Liu, Wei, Su, Hang, Wu, Baoyuan, Zhang, Tong, Zhu, Jun   +6 more
core   +1 more source

Pooling Faces: Template based Face Recognition with Pooled Face Images

, 2016
We propose a novel approach to template based face recognition. Our dual goal is to both increase recognition accuracy and reduce the computational and storage costs of template matching.
Choi, Jongmoo, Harel, Shai, Hassner, Tal, Kim, Jungyeon, Masi, Iacopo, Medioni, Gerard, Natarajan, Prem   +6 more
core   +1 more source

Relaxed 2-D Principal Component Analysis by $L_p$ Norm for Face Recognition

, 2019
A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation ...
A d’Aspremont, A Pentland, D Meng, DM Witten, H Shen, H Wang, H Zou, I Jolliffe, J Wang, J Yang, J Ye, L Sirovich, L Zhao, M Kirby, M Turk, M Zhao, N Kwak, N Kwak, Q Chang, R Ma, X Li, Z Jia, Z Jia, Z Jia, Z Jia, Z Jia, Z Liang, Z-G Jia, ZZ Liang   +28 more
core   +1 more source

Invface: inversion-based synthetic face recognition

Discover Artificial Intelligence
Facial recognition technology has achieved remarkable accuracy across various applications, but its reliance on large-scale real face datasets raises significant privacy and ethical concerns.
Zhifang Sun, Sukumar Letchmunan, Wulfran Fendzi Mbasso, K. Tamilselvan, Zhe Liu   +4 more
doaj   +1 more source

Measuring Face Recognition Performance: Investigating Cambridge Face Memory Test and Glasgow Face Matching Test Performances in Groups with Different Face Recognition Experience

Neuropsychiatric Investigation, 2020
Objective: The main objective of this study was to assess the reliability of the Cambridge Face Memory Test (CFMT) and the Glasgow Face Matching Test (GFMT) for the Turkish sample.
Aycan KAPUCU, Ayşegül AYDINLIK, Sonia AMADO   +2 more
doaj   +1 more source