Object Recognition and Tracking for Enhanced Security Using Computer Vision
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64650-8_13
Reference21 articles.
1. Maan, S., Tyagi, A., Kumar, S., Kumar, A.: Security and surveillance using computer vision. Int. J. Comput. Appl. 176, 30–35 (2020). https://doi.org/10.5120/ijca2020920280
2. Gautam, K.S., Parameswaran, L., Thangavel, S.K.: Computer vision based asset surveillance for smart buildings. J. Comput. Theor. Nanosci. 17, 456–463 (2020). https://doi.org/10.1166/jctn.2020.8691
3. Abdulhussein, A.A., Kuba, H.K., Alanssari, A.N.A.: Computer vision to improve security surveillance through the identification of digital patterns. In: 2020 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) (2020). https://doi.org/10.1109/icieam48468.2020.9112022
4. Rehman, A., Saba, T., Khan, M.Z., Damaševičius, R., Bahaj, S.A.: Internet-of-Things-based suspicious activity recognition using multimodalities of computer vision for smart city security. Secur. Commun. Networks. 2022, 1–12 (2022). https://doi.org/10.1155/2022/8383461
5. Sonavane, C., Kulkarni, P., Podey, O., Rewane, P.: Smart surveillance and tracking system using resnet and tesseract-OCR. In: 2021 IEEE Pune Section International Conference (PuneCon) (2021). https://doi.org/10.1109/punecon52575.2021.9686493
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