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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24205
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Total Authors : 24597
Total Reviewer : 847
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| Paper Title: | Face Recognition Attendance System |
| Authors Name: | Dr.Preethi Jeevan , Ballannagari Kushitha , C.Chandrashekar , B.Akshaya |
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IJRTI_211712
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| Published Paper Id: | IJRTI2604214 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | Conventionally, attendance management at educational institutes relies on a manual or partly automatic approach that is not only inefficient but also prone to errors and potential misuse, such as fake attendance. This paper highlights the development of an automated attendance management system that uses deep learning–based face recognition technology to automate attendance recording. The proposed solution relies on a full-stack approach that incorporates ReactJS on the front-end to build a responsive user interface for the system while the back-end utilizes FastAPI to handle authentication and interactions between the frontend and the relational database used for storing user data, including user roles. DeepFace technology is employed to create an automated pipeline for face recognition, whereby facial images are converted into embeddings before identity matching is performed by calculating cosine similarity between the embeddings. Access controls are provided to various categories of users based on their roles, thus making it possible for administrators to perform efficient user management, while faculty members are able to mark attendance in class for the enrolled students in real-time. Users are then allowed to access attendance records from dashboards for monitoring purposes.The experimental results show that this system is very effective in reducing manual effort and increasing the accuracy of the attendance system under normal circumstances. However, its effectiveness can be affected by various hardware constraints as well as external factors such as lighting. Overall, the suggested approach provides a very scalable solution for attendance management using AI. |
| Keywords: | Face Recognition, Attendance System, Deep Learning, FastAPI, React |
| Cite Article: | "Face Recognition Attendance System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b580-b584, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604214.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604214
Registration ID:211712
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b580-b584 Country: Medchal, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604214 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604214 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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