Identifying Actual Working Hours of Drivers Using Face Recognition

Identifying Actual Working Hours of Drivers Using Face Recognition

Authors

  • Ms. Shelly Shiju George ktu
  • Vinu Reji John

DOI:

https://doi.org/10.5281/zenodo.6367449

Abstract

: Identify the challenges that drivers experience in a
car rental system to examine their actual working hours. We
provided an improved method for improving human face
recognition in this paper using LBPH (Local binary pattern
histogram). The key contribution of this paper is about the
live training dataset. In the face recognition process, data and
feature reduction are critical, and researchers have recently
concentrated on the current neural network. As a result, we
used a local binary pattern histogram descriptor to show that
even with standard approaches, there is room for
improvement.

Published

2023-02-23

How to Cite

Ms. Shelly Shiju George, & Vinu Reji John. (2023). Identifying Actual Working Hours of Drivers Using Face Recognition . National Conference on Emerging Computer Applications, 4(1), 216–222. https://doi.org/10.5281/zenodo.6367449
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