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Our project aims to automate the conventional attendance management system for both ends (students and teachers) by using machine learning model of face recognition and a mobile application.

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Grovercode/Face-Recognition-Attendance-Android-App

 
 

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Face-Recognition Attendance: Android App

This repository contains the code for Face Attenance Android app.

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Group 3

Members

Hriday Grover - LIT2019042

Mohsin Ahmed - LIT2019066

Mark Andrew - LIT201940

Bhanu Prakash Singh - LIT201943

Rajat Napalchyal - LIT2019076

Overview

Our project aims to automate the conventional attendance management system for both ends (students and teachers) by using machine learning model of face recognition and a mobile application.

Additionally, the android application counterpart for students and teachers allows for teachers to access Realtime updating of classes and schedules. And using this database and the CNN algorithms done on the live surveillance updating the database, the students can retrieve information about their latest attendance percentage, records for each class they're enrolled in.

Screenshots

Home Screen, Sign up/ Login menu for students and teachers

Screenshot 2021-11-14 165550 Screenshot 2021-11-14 165805

Sign up menu for Students for adding their details and a clear image for the machine learning encodings to process for face recognition.

Screenshot 2021-11-14 170427

Registrations inside Teacher's Menu for adding a class dynamically

Screenshot 2021-11-14 170512

Student Login and Dashboard Portal for accessing their attendance and subjects dynamically

Screenshot 2021-11-14 170637

Detection and working of backend machine learning encodings

Screenshot 2021-11-14 171017

To Run on Android Studio

Clone this repository

git clone https://github.com/Grovercode/Face-Recognition-Attendance-Android-App.git

Open the project in Android Studio and Run.

About

Our project aims to automate the conventional attendance management system for both ends (students and teachers) by using machine learning model of face recognition and a mobile application.

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  • Java 100.0%