Neural network surveillance system
https://doi.org/10.35266/1999-7604-2024-4-3
Abstract
The purpose of the paper is to design and implement an efficient and affordable automatic surveillance system, which can operate in real time and integrate with existing surveillance systems. The method presented includes analyzing existing solutions on the market, selecting and training a profound learning model for objects detection, developing user interfaces, containerizing of the application and testing the system in a real-world environment. The result is a system capable of detecting objects of interest in real time using neural networks and notifying the user of the detected items. This system is designed for public places like airports, railway stations, schools, and other institutions needing enhanced security
About the Authors
N. E. Vasilenko
Surgut State University, Surgut
Russian Federation
Russian Federation
Master’s Degree Student
N. A. Medvedeva
Surgut State University, Surgut
Russian Federation
Russian Federation
Senior Lecturer
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Review
For citations:
Vasilenko N.E., Medvedeva N.A. Neural network surveillance system. Proceedings in Cybernetics. 2024;23(4):25-33. (In Russ.) https://doi.org/10.35266/1999-7604-2024-4-3
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