Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Fraud Face Detection at ATM using YOLOv5

Authors
Modalavalasa Divya1, *, K. B. Anusha1, Ch. Krishna Veni1, T. Sai Sriya1, K. Jagadeesh Kumar1, S. Siresha1, R. Bala Vinoth1
1Department of Computer Science & Engineering, Aditya Institute of Technology and Management, Tekkali, 532201, India
*Corresponding author. Email: divya.modalavalasa@gmail.com
Corresponding Author
Modalavalasa Divya
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_44How to use a DOI?
Keywords
Artificial Intelligence; Prompt Engineering; Natural Language Processing; MERN Stack
Abstract

The increasing of fraudulent activities including wearing helmets and masks in the ATM premises. This System is designed to enhance security and efficiency in automated teller machine operations. This project focuses on real-time surveillance, wearing masks, helmets, anomaly detection, multiple face detection mitigate risks associated with fraudulent activities.It employs advanced technologies like video analytics and machine learning to identify suspicious activities, ensuring a secure and seamless banking experience for users. This System includes features such as remote monitoring through a centralized dashboard, alert notifications for unusual transactions or security breaches and a comprehensive reporting module for analyzing ATM performance and user behavior. By integrating cutting-edge technologies, this project aims to provide a robust solution for ATM management and security in the evolving landscape of banking services.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
978-94-6463-471-6
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_44How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Modalavalasa Divya
AU  - K. B. Anusha
AU  - Ch. Krishna Veni
AU  - T. Sai Sriya
AU  - K. Jagadeesh Kumar
AU  - S. Siresha
AU  - R. Bala Vinoth
PY  - 2024
DA  - 2024/07/30
TI  - Fraud Face Detection at ATM using YOLOv5
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 453
EP  - 463
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_44
DO  - 10.2991/978-94-6463-471-6_44
ID  - Divya2024
ER  -