Ensemble of Convolutional Neural Networks for Face Recognition

被引：3
|
作者：
Mohanraj, V. [1 ]
Chakkaravarthy, S. Sibi [1 ]
Vaidehi, V. [2 ]
机构：
[1] Anna Univ, Madras Inst Technol, Dept Elect Engn, Chennai, Tamil Nadu, India
[2] VIT Univ, Sch Comp Sci & Engn, Chennai, Tamil Nadu, India
来源：
RECENT DEVELOPMENTS IN MACHINE LEARNING AND DATA ANALYTICS | 2019年 / 740卷
关键词：
Face recognition; CNN; Pre-trained models; Machine learning; Computer vision; SCALE;
D O I：
10.1007/978-981-13-1280-9_43
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Convolutional Neural Networks (CNN) are becoming increasingly popular in large-scale image recognition, classification, localization, and detection. Existing CNN models use the single model to extract the features and the recognition accuracy of these models is not adequate for real-time applications. In order to increase the recognition accuracy, an Ensemble of Convolutional Neural Networks (ECNN) based face recognition is proposed. The proposed model addresses the challenges of facial expression, aging, low resolution, and pose variations. The proposed ECNN model outperforms the existing state of the art models such as Inception-v3, VGG16, VGG19, Xception and ResNet50 CNN models with a Rank-5 accuracy of 97.12% on Web Face dataset and 100% on YouTube face dataset.
引用
收藏
页码：467 / 477
页数：11
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