1. Sun, P.: Deep learning technology applications for video surveillance. Sourcesecurity. https://www.sourcesecurity.com/insights/deep-learning-technology-applications-video-surveillance-co-14319-ga.21460.html. Accessed 31 Jan 2023
2. Advanced Sciences and Technologies for Security Applications;S Ahmed,2021
3. Chen, J., Li, K., Deng, Q., Li, K., Yu, P.S.: Distributed deep learning model for intelligent video surveillance systems with edge computing. IEEE Trans. Industr. Inf. (2020). https://doi.org/10.1109/TII.2019.2909473
4. Kumar, B.C., Punitha, R., Mohana: YOLOv3 and YOLOv4: multiple object detection for surveillance applications. In: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli, India, pp. 1316–1321 (2020). https://doi.org/10.1109/ICSSIT48917.2020.9214094
5. Alqatawneh, S., Jaber, K.M., Salah, M., Dalal, B.Y., Alqatawneh, O., Abulahoum, A.: Employing of object tracking system in public surveillance cameras to enforce quarantine and social distancing using parallel machine learning techniques. Int. J. Adv. Soft Comput. Appl. 13(3), 170–180 (2021)