Online students’ attendance monitoring system in classroom using UHF RFID, which can automatically record students’ attendance at lectures or laboratories 14. However, the UHF are not widely used in universities and colleges. In fact, HF RFID cards are widely used as IDs of students in campus management.

An automated attendance system that consists of a web system for entire organization to record attendance. Each Class room or department has its own login. On login the class faculty can see a list of students or members registered under it.

The GtkRadiant team is working onversion 1.6, which is actually a successor of GtkRadiant 1.4.Because some people, me included, prefer the distinct look and feel ofGtkRadiant 1.5 over the 1.4/1.6 branch, the Xonotic team forked GtkRadiant 1.5as NetRadiant.This build was created from NetRadiant's ingar/netradiant-ing branch,which can be found in the.The most notable difference between this branch and master is support for the WebP image format.The release also adds a number of gamepacks which are not included in repository.I did not write GtkRadiant or NetRadiant. While I do commit patches,I mostly download the source code, build executables and add documentation and game packs.My goal is to provide a package that is easy to install for anyone who might need it.

The faculty may take the attendance and mark the present students using checkbox provided in front of every student name. This attendance sheet is stored and sent to the central administrator of the organization and stored there. The system has an admin login.

The admin may check all attendance data, press a button to see defaulter list, search for particular student attendance by name, search class attendance and generate excel reports.

Abstract

Traditionally, the attendance of students has been a major concern for the colleges and the faculty has to spend a lot of time and is a tedious job to mark attendance manually. Current biometric attendance system is not automatic that’s why wastes a lot of time, difficult to maintain and requires a queue for scanning fingerprints to mark their attendance. In Modern era everyone has Smartphone and connected via internet every time. In this paper attendance monitoring will be done through smart phone available with almost all faculty members. Some of popular object detection algorithms are back propagation neural network, region based convolution network (RCNN), faster RCNN, single shot detector. Our unified structure is based on YOLO V3 (You only look once) algorithm for face detection and Microsoft Azure using face API for face recognition (face database). The unique part is camera installed in classroom will take picture twice one at the start and one at the end to ensure students has attended complete class. YOLO V3 will first count the students in an image followed by identifying faces as known and unknown generating spreadsheets separately and an email is send at the end of month to students, parents and faculty. The designed system performs efficient in real time implementation for counting and detection. Our entire system has proven to gather high accuracy in face detection and performance.

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