Face Recognition Based Smart Attendance System

Raj, A Arjun; Shoheb, Mahammed; Arvind, K.R.; Chethan, K S

doi:10.1109/iciem48762.2020.9160184

Cited by 23 publications

(5 citation statements)

References 6 publications

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“…Through the utilization of a face recognition algorithm, the system first detects faces in the provided images or video streams. Subsequently, it undergoes two crucial decision-making processes as documented in face verification [11], which assesses if the detected face matches any of the trained faces, and Face or No face decision, which determines whether a face is present in the image or if there's no face detected. These distinct stages are pivotal in ensuring the system's accuracy and effectiveness.…”

Section: Phase 3: Face Detectionmentioning

confidence: 99%

Attendance management system using face recognition

Jadhav,

Kamble,

Rathod

et al. 2024

IJ-AI

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<p>Traditional attendance systems consist of registers marked by teachers, leading to human error and a lot of maintenance. Time consumption is a key point in this system. We wanted to revolutionize the digital tools available in today's time i.e., facial recognition. This project has revolutionized to overcome the problems of the traditional system. Face recognition and marking the present is our project. A database of all students in the class is kept in single folder, and attendance is marked if each student's face matches with one of the stored faces. Otherwise, the face is ignored and not marked for attendance. In our project, face detection (machine learning) is used.</p>

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Section: Phase 3: Face Detectionmentioning

confidence: 99%

Attendance management system using face recognition

Jadhav,

Kamble,

Rathod

et al. 2024

IJ-AI

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“…In [1], Arjun Raj technique called histogram equalization is done. Once the faces are recognized, the recognized faces will be compared with the face images present in the database to inform whether student is present or not.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Review on Attendance System Using Face Recognition Technology

2023

IRJMETS

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Attendance tracking systems play a crucial role in various sectors, including education, business, and government. Conventional strategies of attendance recording were taking sign of student or calling the student which are tedious, time consuming and vulnerable to proxies. There are various technologies that can be used to develop an automated attendance system like figure print scanner, face recognition, etc. With the advancement of technology, face recognition has emerged as a powerful tool for automating attendance management. This review paper provides an analysis of attendance systems that utilize face recognition techniques. We explore the underlying technology, applications, benefits, recent developments, and future prospects in the field of face recognition-based attendance systems. The System first create students' database to train model to be developed. The System captures the image and preprocess it with Generative Adversarial Network (GAN), grayscale conversion and histogram equalization. Then the faces will be detected using 68 landmarks of faces and Deep Neural Network (DNN). The resultant image will be used for feature extraction using Gabor Filters. After this face recognition algorithms like K-Nearest Neighbor (KNN), Convolutional Neural Network (CNN) and Local Binary Pattern Histogram (LBPH) will be comparatively applied on it. Since the article is concerned with the attendance system, The Eigenface method for face recognition is preferred over other face recognition algorithms. The recognized faces will be cross checked with the database images. If the match founds the student is present otherwise not. The students will be notified about their attendance using SMS.

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“…Email notification of the absence of the absentee's employee or ward is sent to the absentee's manager or parents, as appropriate. This project's goal is to provide new features to already existing projects, such as massive data storage and quick processing, while using less expensive technology [9]. The Local Binary Pattern Histogram (LBPH) face recognizer is used by the system known as Intelligent Attendance System based on Face Recognition to identify the person's face in real time [10].…”

Section: Related Workmentioning

confidence: 99%

An Intelligent Sensor based Automatic Attendance Management System Using IoT

Meenakshi¹,

Leelarani²,

Shopika³

et al. 2022

IJRITCC

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The need for intelligent and distributed monitoring systems based on sensor networks of diverse application systems is growing as a result of the field of industrial control in network applications developing so quickly. It is required to check the body temperatures and attendance when students and staffs visit schools and colleges during this COVID 19 pandemic. A solution is developed here for the purpose of tracking temperatures and attendance management using a smart thermometer without being in contact in order to keep social distance. The person (both staff and student) faces are captured by the ESP32 Camera for training and testing purposes. After the training is over, the ESP32 Micro Controller board registers the student or faculty facial image. For attendance purposes, the MLX90614 IR Temperature Sensor will measure the body temperature of students or instructors. Both the collected data and the email-based attendance notification will be transferred to the cloud using IoT. The message "Please leave the college and take care of your health" will be communicated to the person if their temperature exceeds the threshold level.

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Face Recognition Based Smart Attendance System

Cited by 23 publications

References 6 publications

Attendance management system using face recognition

Attendance management system using face recognition

A Comprehensive Review on Attendance System Using Face Recognition Technology

An Intelligent Sensor based Automatic Attendance Management System Using IoT

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