scholarly journals Smart Attendance Management System Using Face Recognition

2021 ◽  
pp. 706-711
Author(s):  
K. V. Prasad Reddy ◽  
R. Chaitanya Latha ◽  
M. Lohitha ◽  
R. Sonia ◽  
A. B. Usha
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Face Recognition ◽  
Conventional Method ◽  
Management System ◽  
Reading And Writing ◽  
Manual Method

To Maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The smart attendance management will replace the manual method, which takes a lot of time consuming and difficult to maintain. There are many biometric processes, in that face recognition is the best method. Here we are using the computer vision which is a field of deep learning that is used for the camera reading and writing and using TkInter to create a GUI application.

scholarly journals Automatic Attendance Management System under Unconstrained Video using Face Recognition

2020 ◽  
Vol 9 (10) ◽  
pp. 229-232
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Management System ◽  
Traditional Method ◽  
Surveillance Camera ◽  
Recognition Systems ◽  
End To End ◽  
Learning By Using

Attendance Management System under unconstrained video using face recognition technology has made a great variation from the traditional method of attendance marking system. This attendance management system has been developed under the domain of Deep Learning by using Face recognition. Automatic Attendance Management under unconstrained video using face recognition systems which automatically mark attendance by detecting end to end face from the frames obtained from live stream video of surveillance camera which placed in center of the classroom. From the recognized faces, it will be compared with stored images in database, then the attendance report will be generated and it also provides attendance reports to parents of the absentee’s student.

scholarly journals A Study of The Convolutional Neural Networks Applications

2019 ◽  
Vol 3 (2) ◽  
pp. 31-40 ◽  
Author(s):  
Ahmed Shamsaldin ◽  
Polla Fattah ◽  
Tarik Rashid ◽  
Nawzad Al-Salihi
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Natural Language Processing ◽  
Face Recognition ◽  
Convolutional Neural Networks ◽  
Language Processing ◽  
Text Classification ◽  
Scene Labeling ◽  
Real World Problems

At present, deep learning is widely used in a broad range of arenas. A convolutional neural networks (CNN) is becoming the star of deep learning as it gives the best and most precise results when cracking real-world problems. In this work, a brief description of the applications of CNNs in two areas will be presented: First, in computer vision, generally, that is, scene labeling, face recognition, action recognition, and image classification; Second, in natural language processing, that is, the fields of speech recognition and text classification.

scholarly journals Masked Face Analysis via Multi-Task Deep Learning

2021 ◽  
Vol 7 (10) ◽  
pp. 204
Author(s):  
Vatsa S. Patel ◽  
Zhongliang Nie ◽  
Trung-Nghia Le ◽  
Tam V. Nguyen
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Face Recognition ◽  
Face Mask ◽  
Learning Model ◽  
Unified Framework ◽  
Improve Performance ◽  
Face Analysis ◽  
And Gender ◽  
Deep Learning Model

Face recognition with wearable items has been a challenging task in computer vision and involves the problem of identifying humans wearing a face mask. Masked face analysis via multi-task learning could effectively improve performance in many fields of face analysis. In this paper, we propose a unified framework for predicting the age, gender, and emotions of people wearing face masks. We first construct FGNET-MASK, a masked face dataset for the problem. Then, we propose a multi-task deep learning model to tackle the problem. In particular, the multi-task deep learning model takes the data as inputs and shares their weight to yield predictions of age, expression, and gender for the masked face. Through extensive experiments, the proposed framework has been found to provide a better performance than other existing methods.

scholarly journals Smart Attendance Monitoring System with Computer Vision Using IOT

2021 ◽  
Author(s):  
Ashwin Raj ◽  
Aparna Raj ◽  
Imteyaz Ahmad
Keyword(s):  
Computer Vision ◽  
Face Recognition ◽  
Monitoring System ◽  
Conventional Method

The main aim of this project is to create a smart attendance monitoring system which will use the concept of face recognition to identify students. On the basis of this a database will be created containing the information of attendance date wise. Apart from reducing time it will also help in replacing the laborious conventional method of using logbooks. The system also has the feature to send emails to the administrator about the student ‘s attendance status at the time of recognition itself. At the time of closing of the camera absentees’ names will be called out.

scholarly journals Development of the "smart library" application using the Intel Distribution of OpenVINO toolkit

2019 ◽  
Author(s):  
Евгений Васильев ◽  
Evgeniy Vasil'ev ◽  
Валентина Кустикова ◽  
Valentina Kustikova ◽  
Иван Вихрев ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Deep Learning ◽  
Face Recognition ◽  
Source Code ◽  
Face Features ◽  
Machine Learning Model ◽  
Library Users ◽  
The Face

We represent a case study of using deep learning and computer vision library - the Intel Distribution of OpenVINO toolkit. We develop the automated “smart library” using DL and computer vision methods implemented in OpenVINO toolkit. The application involves the registration of the reader (adding information and photos of the new user); updating the machine learning model that describes the face features of the library users; authorization of the reader through face recognition; receiving and returning books by comparing the cover image with the database of flat images available in the library of books. The source code of the application is free available on GitHub: https://github.com/itlab-vision/openvino-smart-library. The developed application is planned to be published as a sample of the OpenVINO toolkit.

scholarly journals Face with Mask Detection and Recognition for Smart Attendance System

2021 ◽  
Vol 9 (VII) ◽  
pp. 1586-1591
Author(s):  
Shweta Panjabrao Dhawale
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Face Recognition ◽  
Face Detection ◽  
Face Mask ◽  
Learning Framework ◽  
The Face ◽  
Face Detection And Recognition ◽  
Python Programming ◽  
Detection And Recognition

In this paper we will see the face mask detection and recognition for smart attendance system. In current pandemic situation our proposed system is very useful. We have used here face algorithm technique, python programming and to capture the images open cv is used., open cv2 now comes with a very new face recognizer class for the face recognition and popular computer vision liberaay started by intel in 1999. Open cv released under BSD licence that’s why used in the academic projects. We have used the concept of deep learning framework for the detection of faces. our aim is to present the study of previous attempts at face detection and recognition for smart attendance system by using deep learning .these is rapidly growing technology with its application in various aspects.

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