Smart Attendance System Using Deep Learning Convolutional Neural Network

被引：0

作者：

Pooja, I ^{[1
]}

Gaurav, J. ^{[1
]}

Devi, C. R. Yamuna ^{[1
]}

Aravindha, H. L. ^{[1
]}

Sowmya, M. ^{[1
]}

机构：

[1] Dr Ambedkar Inst Technol, Bangalore 560056, Karnataka, India

来源：

CYBER-PHYSICAL SYSTEMS AND DIGITAL TWINS | 2020年 / 80卷

关键词：

Convolutional neural network (CNN); Deep learning; AlexNet; Transfer learning;

D O I：

10.1007/978-3-030-23162-0_31

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Image recognition has been playing an increasingly larger role in the modern life like driver assistance systems, medical imaging system, quality control system to name a few. Artificial Neural Network models are extensively used for the above purposes due to their reliable success. One such update used here is the convolutional neural network (CNN, or ConvNet). This paper highlights the importance of pre-trained neural networks as well as the significance of Deep Learning used in the field of Academics and Advancement which is implemented in MATLAB Software. Smart Attendance Systems involves the image (face) detection and analyzes the data accurately. This approach solves the time consuming traditional method of attendance system and paves way for new advanced technologies.

引用

页码：343 / 356

页数：14

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