Comparison of Face Classification with Single and Multi-model base on CNN
- 18 November 2020
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)
Abstract
Since the coronavirus disease 2019 (COVID-19) outbreak has spread across the country, our research applies to remind the people to wear a face mask when we go outside because a facial image detection and classification method will be used to authentication and authorization. This paper has shown that our created models based on CNN can detect the face mask-wearing, glasses-wearing, and gender with comparison two models. We training model with mix public datasets such as WIDER FACE, AFW, and MAFA. Moreover, we use VGG-Face to pre-train the model for the advance detection rate.Keywords
This publication has 10 references indexed in Scilit:
- Re-Ranking High-Dimensional Deep Local Representation for NIR-VIS Face RecognitionIEEE Transactions on Image Processing, 2019
- Deep Discriminative Representation Learning for Face Verification and Person Re-Identification on Unconstrained ConditionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Feature Extraction using Convolution Neural Networks (CNN) and Deep LearningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Robust human re-identification using mean shape analysis of face imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Pose-Invariant Face Alignment with a Single CNNPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- AcFR: Active Face Recognition Using Convolutional Neural NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Detecting Masked Faces in the Wild with LLE-CNNsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Distance Metric Learning Using Privileged Information for Face Verification and Person Re-IdentificationIEEE Transactions on Neural Networks and Learning Systems, 2015
- DeepFace: Closing the Gap to Human-Level Performance in Face VerificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Improvement of Face Recognition by Eyeglass RemovalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010