Author:
Binti Mat Kasim Nur Ateqah,Binti Abd Rahman Nur Hidayah,Ibrahim Zaidah,Abu Mangshor Nur Nabilah
Abstract
Face recognition is one of the well studied problems by researchers in computer visions. Among the challenges of this task are the occurrence of different facial expressions like happy or sad, and different views of the images such as front and side views. This paper experiments a publicly available dataset that consists of 200,000 images of celebrity faces. Deep Learning technique is gaining its popularity in computer vision and this paper applies this technique for face recognition problem. One of the techniques under deep learning is Convolutional Neural Network (CNN). There is also pre-trained CNN models that are AlexNet and GoogLeNet, which produce excellent accuracy results. The experimental results indicate that AlexNet is better than basic CNN and GoogLeNet for face recognition.
Publisher
Institute of Advanced Engineering and Science
Subject
Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Information Systems,Signal Processing
Cited by
10 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Movie Character Recognition from Video and Image using AI;International Journal of Advanced Research in Science, Communication and Technology;2024-04-06
2. Deep fake detection and classification using error-level analysis and deep learning;Scientific Reports;2023-05-08
3. Wavelet transformation and vertical stacking based image classification applying machine learning;Biomedical Signal Processing and Control;2023-01
4. Image Recognition Algorithm Based on Deep Learning;2022 International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME);2022-06
5. Specification and Operation of Privacy Models for Data Streams on the Edge;2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC);2022-05