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Real-time Monitoring of Workforce: An approach based on Deep Features

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Sadique K.M., Amos R.

Sadique K.M. and Amos R.. Real-time Monitoring of Workforce: An approach based on Deep Features. International Journal of Computer Applications 183(29):13-16, October 2021. BibTeX

	author = {Sadique K.M. and Amos R.},
	title = {Real-time Monitoring of Workforce: An approach based on Deep Features},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2021},
	volume = {183},
	number = {29},
	month = {Oct},
	year = {2021},
	issn = {0975-8887},
	pages = {13-16},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2021921668},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In this paper, we monitor real-time workforce attendance. At first, we record the check-in and check-out of the workforce. Next, keep track of their movements at various premises within the organization. Finally alarm the administrator for unauthorized movement. In order to meet these requirements, we extracted state-of-the-art deep learning-based features by utilizing AlexNet. Extensive experiments were conducted on our created dataset. From the experiments it was revealed that extracted features substantially perform better.


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  10. Sadique K M pursuing his Masters in Computer Applications at Maharaja Institute of Technology Mysore, His research interests include computer vision and machine learning.
  11. Amos R, Assistant Professor, Department of Masters in Computer Applications at Maharaja Institute of Technology Mysore. His research Interests include Computer vision, machine learning, and data science.


Real-time monitoring, attendance system, unauthorized movement, deep learning, AlexNet.