Student Attendance Using Deep Entity Naming Technique

Student attendance using deep entity naming technique is a system in which we are using two technologies Deep learning and face recognition. This system can be implemented everywhere easily which will help to reduce the cost. We are going to detect the student face and extract all the facial feature

Project Title

Student Attendance Using Deep Entity Naming Technique

Project Area of Specialization

Artificial Intelligence

Project Summary

Student attendance using deep entity naming technique is a system in which we are using two technologies Deep learning and face recognition. This system can be implemented everywhere easily which will help to reduce the cost. We are going to detect the student face and extract all the facial features by applying HOG algorithm. Supervised learning approach will be used in our system.

With the help of STUDENT (Student Attendance Using Deep Entity Naming Technique) attendance can be marked by live video face cam. Face recognition can properly answer the question "Is this the right recognized person”. Face detection combines facial features to identify whether the person is recognized or not. Face recognition is one of the biometric information processes, its application is easier and its working range is wider than that of other biometric information processes such as fingerprint, iris scanning, signature, and so on. Face detection and recognition are two themes. Face detection is done on real-time face cam, skin like area segmentation, facial feature extraction are the key points that extracts the image of the face of student.

Student attendance using deep entity naming technique is a system in which we are using two technologies Deep learning and face recognition. This system can be implemented everywhere easily which will help to reduce the cost. We are going to detect the student face and extract all the facial features by applying HOG algorithm. Supervised learning approach will be used in our system.

With the help of STUDENT (Student Attendance Using Deep Entity Naming Technique) attendance can be marked by live video face cam. Face recognition can properly answer the question "Is this the right recognized person”. Face detection combines facial features to identify whether the person is recognized or not. Face recognition is one of the biometric information processes, its application is easier and its working range is wider than that of other biometric information processes such as fingerprint, iris scanning, signature, and so on. Face detection and recognition are two themes. Face detection is done on real-time face cam, skin like area segmentation, facial feature extraction are the key points that extracts the image of the face of student.

Project Objectives

The goal behind this project is to achieve high accuracy in face recognition with high frame rates in live video processing and reduce the maximum probability of errors during marking attendance.

Objectives:

Attendance:

Attendance through face recognition is not only efficient but also the time saving. By developing such system will save time. The main objective of this work is to make the attendance marking and management system efficient, time saving, simple and easy.

Project Implementation Method

Components, Libraries, Web Services and stubs

• pandas
• Cv2
• Face recognition
• Os
• Datetime
• Mysql.connector

Webservices:

• HTTPS

Tools and Techniques

Tools

• Pycharm
• Mysql(DB)
• Visio

Technologies

• HOG
• Python
• Html
• PHP
• CSS

Benefits of the Project

Over the once decade, taking student attendance process has been developed and changed. The purpose of this development is the desire to automate, speed up and save time. Although, the attendance systems are around us everyplace. School teachers are still using a traditional way to record student’s attendance through calling out student’s name. This way of marking student attendance is very time consuming. In this design, our goal is to reduce time waste and automate the process. Our system uses facial recognition technology to record the attendance through a digital camera that detects and recognizes faces and compare those faces with students face images stored in database. Sometimes teachers have quite a significant number of student and it gets hard to keep tracking and marking all their attendance. Facial recognition is generally used in some offices to mark attendance of their employees

Technical Details of Final Deliverable

32-bit operating system

The system is designed such a way so that it can be run on any low device. The minimum specification required to run this system are.

•  Operating system: Linux- Ubuntu 16.04 to 17.10, or Windows 7 to 10
• Camera: HD camera is recommended

Final Deliverable of the Project

Software System

Core Industry

Education

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Quality Education

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com