Real-time face recognition based on IoT: A comparative study between IoT platforms and cloud infrastructures

2020 ◽  
Vol 26 (2) ◽  
pp. 155-168
Author(s):  
Asif Ahmed ◽  
Soumitra Saha ◽  
Sudip Saha ◽  
Md. Younus Bipul ◽  
Syad Md. Imran ◽  
...  
Keyword(s):  
Face Recognition ◽  
Comparative Study ◽  
Real Time ◽  
Iot Platforms ◽  
Cloud Infrastructures

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

Real Time Gender and Age Prediction using Deep Learning Techniques

2020 ◽  
Vol 9 (6) ◽  
pp. 797-801
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Real Time ◽  
Vital Role ◽  
Learning Techniques ◽  
Gender And Age ◽  
The Face ◽  
And Gender ◽  
Gender Detection ◽  
Age Prediction

Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.

COMPARATIVE STUDY OF SPECIFICITY AND SENSITIVITY FOR IHHNV DETECTION BETWEEN REAL-TIME PCR AND LAMP METHODS

2010 ◽  
Vol 36 (5) ◽  
pp. 984-989
Author(s):  
Zhe ZHAO ◽  
Chun-Hua REN ◽  
Xiao JIANG ◽  
Lü-Ping ZHANG ◽  
Juan FENG ◽  
...  
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Real Time Pcr ◽  
Specificity And Sensitivity

Development of the Facial-Color Simulator with Real-Time Face Recognition

2007 ◽  
Vol 6 (2) ◽  
pp. 53-64
Author(s):  
Takao Makino ◽  
Toshiya Nakaguchi ◽  
Norimichi Tsumura ◽  
Koichi Takase ◽  
Saya Okaguchi ◽  
...  
Keyword(s):  
Face Recognition ◽  
Real Time

scholarly journals A novel approach to optimize the production cost of railway coaches of India using situational-based composite triangular and trapezoidal fuzzy LPP models

2021 ◽  
Author(s):  
Rakesh Kumar ◽  
Gaurav Dhiman ◽  
Neeraj Kumar ◽  
Rajesh Kumar Chandrawat ◽  
Varun Joshi ◽  
...  
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Production Cost ◽  
Upper Bounds ◽  
Production Costs ◽  
Cost Data ◽  
Novel Approach ◽  
Membership Grade ◽  
Minimum Costs

AbstractThis article offers a comparative study of maximizing and modelling production costs by means of composite triangular fuzzy and trapezoidal FLPP. It also outlines five different scenarios of instability and has developed realistic models to minimize production costs. Herein, the first attempt is made to examine the credibility of optimized cost via two different composite FLP models, and the results were compared with its extension, i.e., the trapezoidal FLP model. To validate the models with real-time phenomena, the Production cost data of Rail Coach Factory (RCF) Kapurthala has been taken. The lower, static, and upper bounds have been computed for each situation, and then systems of optimized FLP are constructed. The credibility of each model of composite-triangular and trapezoidal FLP concerning all situations has been obtained, and using this membership grade, the minimum and the greatest minimum costs have been illustrated. The performance of each composite-triangular FLP model was compared to trapezoidal FLP models, and the intense effects of trapezoidal on composite fuzzy LPP models are investigated.

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