Paper Info
Title
Deep learning-based intelligent face recognition in IoT-cloud environment.
Abstract
In recent years, the Internet-of-Things (IoT) technology is being used in many application areas such as healthcare, video surveillance, transportation etc. The massive adoption and growth of IoT in these areas are generating a massive amount of data. For example, IoT devices such as cameras are generating a huge amount of images when used in hospital surveillance scenarios. Here, face recognition is an important element that can be used for securing hospital facilities, emotion detection and sentiment analysis of patients, detecting patient fraud, and hospital traffic pattern analysis. Automatic and intelligent face recognition systems have high accuracy in a controlled environment; however, they have low accuracy in an uncontrolled environment. Also, the systems need to operate in real-time in many applications such as smart healthcare. This paper suggests a tree-based deep model for automatic face recognition in a cloud environment. The proposed deep model is computationally less expensive without compromising the accuracy. In the model, an input volume is split into several volumes, where a tree is constructed for each volume. A tree is defined by its branching factor and height. Each branch is represented by a residual function, which is constituted by a convolutional layer, a batch normalization, and a non-linear function. The proposed model is evaluated in various publicly available databases. A comparison of performance is also done with state-of-the-art deep models for face recognition. The results of the experiments demonstrate that the proposed model achieved accuracies of 98.65%, 99.19%, 95.84% on FEI, ORL, and LFW databases, respectively.
Year
DOI
Venue
2020
10.1016/j.comcom.2020.01.050
Computer Communications
Keywords
Field
DocType
Deep neural network,Intelligent face recognition,Healthcare-IoT,Cloud environment
Data mining,Residual,Facial recognition system,Normalization (statistics),Airfield traffic pattern,Computer science,Sentiment analysis,Internet of Things,Real-time computing,Artificial intelligence,Deep learning,Cloud computing
Journal
Volume
ISSN
Citations 
152
0140-3664
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Mehedi Masud17726.95
Ghulam Muhammad210615.27
Hesham Alhumyani363.36
Sultan S. Alshamrani473.89
Omar Cheikhrouhou56611.71
S. Ibrahim6295.07
Mohammod Shamim Hossain726834.68