Capturing Student’s Attendance Using Face Recognition

Open Access

Year : 2023 | Volume : | : | Page : –
By

Maahi Khemchandani

Hrushikesh Zore

Siddhant Patil

Rohan Shinde

  1. Students Saraswati College of Engineering Navi-Mumbai, Maharashtra India
  2. Students Saraswati College of Engineering Navi-Mumbai, Maharashtra India
  3. Students Saraswati College of Engineering Navi-Mumbai, Maharashtra India
  4. Professor Saraswati College of Engineering Navi-Mumbai, Maharashtra India

Abstract

In instructive foundations, organizations, and different associations, one of the fundamental measures is to keep a record of individuals present every day. Participation Management subsequently turns into a significant objective for the advancement and uprightness of any association. Equipment based participation frameworks that store values in a data set presently exist and are the most well-known record global positioning frameworks found in associations. There are some programmed participations making frameworks that are as of now utilized by numerous foundations. One such framework is the biometric method. Although it is programmed and a stride in front of the customary strategy it neglects to meet the time limitation. The understudy must wait in line for giving participation, which takes time. The proposed framework manages robotizing the participation keep technique in an effective and upgraded way. It follows a counting methodology to keep participation and stores it in the framework. This venture presents a compulsory participation stamping framework, without any sort of impedance with the ordinary instructing method.

Keywords: Face recognition, machine learning, deep learning, face detection, student’s attendance

How to cite this article: Maahi Khemchandani, Hrushikesh Zore, Siddhant Patil, Rohan Shinde. Capturing Student’s Attendance Using Face Recognition. International Journal of Computer Aided Manufacturing. 2023; ():-.
How to cite this URL: Maahi Khemchandani, Hrushikesh Zore, Siddhant Patil, Rohan Shinde. Capturing Student’s Attendance Using Face Recognition. International Journal of Computer Aided Manufacturing. 2023; ():-. Available from: https://journals.stmjournals.com/ijcam/article=2023/view=91293

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Open Access Article
Volume
Received May 12, 2022
Accepted June 13, 2022
Published January 13, 2023