Single sample per person face recognition based on deep convolutional neural network

2017 ◽  
Author(s):  
Junying Zeng ◽  
Xiaoxiao Zhao ◽  
Chuanbo Qin ◽  
Zuoyong Lin
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Single Sample ◽  
Single Sample Per Person

scholarly journals Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Junying Zeng ◽  
Xiaoxiao Zhao ◽  
Junying Gan ◽  
Chaoyun Mai ◽  
Yikui Zhai ◽  
...  
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Convolutional Neural Network ◽  
Traditional Approach ◽  
Deep Convolutional Neural Network ◽  
Single Sample ◽  
Face Database ◽  
Single Sample Per Person ◽  
Sample Method ◽  
Fine Tune

Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be trained, it makes facial variation such as pose, illumination, and disguise difficult to be predicted. To overcome this problem, this paper proposes a scheme combined traditional and deep learning (TDL) method to process the task. First, it proposes an expanding sample method based on traditional approach. Compared with other expanding sample methods, the method can be used easily and conveniently. Besides, it can generate samples such as disguise, expression, and mixed variation. Second, it uses transfer learning and introduces a well-trained deep convolutional neural network (DCNN) model and then selects some expanding samples to fine-tune the DCNN model. Third, the fine-tuned model is used to implement experiment. Experimental results on AR face database, Extend Yale B face database, FERET face database, and LFW database demonstrate that TDL achieves the state-of-the-art performance in SSPP FR.

scholarly journals A Novel Neural Network Method for Face Recognition With a Single Sample Per Person

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 102212-102221 ◽  
Author(s):  
Mohamed Abdelmaksoud ◽  
Emad Nabil ◽  
Ibrahim Farag ◽  
Hala Abdel Hameed
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Single Sample ◽  
Neural Network Method ◽  
Single Sample Per Person ◽  
Network Method

scholarly journals Intelligent Attendance System with Face Recognition using the Deep Convolutional Neural Network Method

2021 ◽  
Vol 1737 (1) ◽  
pp. 012031
Author(s):  
Nurkhamid ◽  
Pradana Setialana ◽  
Handaru Jati ◽  
Ratna Wardani ◽  
Yuniar Indrihapsari ◽  
...  
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Neural Network Method ◽  
Network Method
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