IAA-CNN: Intelligent Attendance Algorithm based on Convolutional Neural Networks

Authors

  • Mario Anzures-Garcia Benemérita Universidad Autónoma de Puebla
  • Luz A. Sánchez Gálvez Benemérita Universidad Autónoma de Puebla. de Ciencias de la Computación.
  • Mariano Larios Gómez Benemérita Universidad Autónoma de Puebla. de Ciencias de la Computación.
  • Arturo Tapia Rodríguez Benemérita Universidad Autónoma de Puebla. de Ciencias de la Computación.
  • Rubén Aguirre Agustín Benemérita Universidad Autónoma de Puebla. de Ciencias de la Computación.

DOI:

https://doi.org/10.61467/2007.1558.2024.v15i5.557

Keywords:

Intelligent Algorithm, Voice Recognition, Image Recognition

Abstract

Nowadays, virtual meetings have increased their usage both in enterprises and educational organizations, since it is necessary to join them to make decisions, conferences, classes, etc. Therefore, there are many platforms for this; such as Microsoft TEAMS, Google Classroom, Zoom, Skype, and many more; simplifying and allowing members of such organizations to work together in a shared space. However, it is possible to waste a lot of time on passing the attendance, and it is very important to carry out it in an educational environment, in which this work is focused. Consequently, an intelligent attendance pass algorithm through voice and image recognition based on convolutional neural networks is proposed. The network ResNet50 is applied to make such recognition; since this network is particularly good for image classification and object detection. Furthermore, analyzed works to pass attendance only focus on generating an assistants list, voice recognition, or image recognition. So, nothing is doing both, voice, and image recognition. Finally, a case study to probe the feasibility of the proposed algorithm is carried out.

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Published

2024-11-29

How to Cite

Anzures-Garcia, M., Sánchez Gálvez, L. A., Larios Gómez, M., Tapia Rodríguez, A., & Aguirre Agustín, R. (2024). IAA-CNN: Intelligent Attendance Algorithm based on Convolutional Neural Networks. International Journal of Combinatorial Optimization Problems and Informatics, 15(5), 51–63. https://doi.org/10.61467/2007.1558.2024.v15i5.557

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