Training Convolutional Neural Network with Logistic Regression Model for Facial Recognition to Monitor Attentiveness in Classrooms

Authors

  • Snehal Chaudhary Assistant professor,Dept of Information Technology, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Shrikala Deshmukh Assistant professor,Dept of Information Technology, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Manisha M. Kasar Assistant professor,Dept of Computer Science Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Gauri Rao Assistant professor,Dept of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Anuradha Sagar Nigade Assistant Professor, Dept of Electronics and Communication Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Aparna Shankar Patil Assistant Professor, Dept of Electronics and Communication Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Meena Chavan Assistant professor, Dept of Electronics and Communication Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune

Keywords:

Facial recognition, feature classification, frame extraction, deep neural network

Abstract

This paper presents a facial recognition system that relies on spectral analysis. Utilizing this technology can enhance classroom security by preventing irregularities such as falsified attendance records or the use of counterfeit identities. The system employs an image recognition algorithm to extract pertinent details from a photograph, subsequently encoding and comparing it with other facial data stored in a database. This image data comprises attributes that highlight distinctions between the system's facial images and those in the image repository. The Facial Recognition System comprises two distinct processing modules: training and recognition. Its efficacy and precision in recognizing individuals were assessed in a high school classroom setting.

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Published

13.12.2023

How to Cite

Chaudhary, S. ., Deshmukh, S. ., Kasar, M. M. ., Rao, G. ., Nigade, A. S. ., Patil, A. S., & Chavan, M. . (2023). Training Convolutional Neural Network with Logistic Regression Model for Facial Recognition to Monitor Attentiveness in Classrooms. International Journal of Intelligent Systems and Applications in Engineering, 12(8s), 592–598. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4231

Issue

Vol. 12 No. 8s (2024)

Section

Research Article

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