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Open Access
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Shiwang Gupta, Pradeep Sain, Sarthak Bhardwaj, Tushar Sharma, Anjuli Dubey,
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- Student, Student, Student, Student, Assistant Professor Department of Computer Science, Poornima College of Engineering, Jaipur, Department of Computer Science, Poornima College of Engineering, Jaipur, Department of Computer Science, Poornima College of Engineering, Jaipur, Department of Computer Science, Poornima College of Engineering, Jaipur, Department of Computer Science, Poornima College of Engineering, Jaipur Rajasthan, Rajasthan, Rajasthan, Rajasthan, Rajasthan India, India, India, India, India
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Abstract
nAttendance tracking stands as a pivotal pillar in organizational management, bearing significant implications for operational efficiency, resource allocation, and fostering accountability. Traditional methodologies for attendance maintenance frequently exhibit deficiencies in terms of precision, security, and scalability, thus necessitating the exploration of avant-garde solutions. This research endeavors to introduce a pioneering approach to attendance upkeep, harnessing the prowess of image processing techniques synergized with artificial intelligence (AI) algorithms to surmount prevailing challenges. Through a comprehensive regimen of rigorous testing and evaluation, we aim to demonstrate the efficacy and dependability of our proposed system in authentic real-world environments. Our methodology involves subjecting the developed system to meticulous scrutiny across various operational contexts, gauging its performance against predefined benchmarks and industry standards. By meticulously analyzing the results derived from these tests, we endeavor to elucidate the system’s capacity to accurately track attendance, ensure data integrity, and adapt to diverse organizational requirements. Furthermore, we prioritize the integration of user feedback into our iterative refinement process, leveraging insights gleaned from end-users to enhance system usability and address any identified shortcomings. The convergence of image processing techniques and AI algorithms affords our system the agility and versatility required to navigate the dynamic landscape of attendance management. Leveraging cutting-edge technology, our approach not only promises to streamline attendance tracking processes but also lays the foundation for a robust framework capable of accommodating future advancements in the field. Through this research endeavor, we aspire to catalyze the evolution of attendance maintenance practices, empowering organizations to optimize operational efficiency and foster a culture of accountability.
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Keywords: artificial intelligence, Attendance tracking, attendance maintenance,
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Image Processing & Pattern Recognition Progress(joipprp)]
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References
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Journal of Image Processing & Pattern Recognition Progress
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| Volume | 11 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | May 6, 2024 | |
| Accepted | July 23, 2024 | |
| Published | July 30, 2024 |
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