A Real-time Crowd Density Level Detection System
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49529-8_12
Reference16 articles.
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2. Sindagi, V.A., Patel, V.M.: A survey of recent advances in CNN-based single image crowd counting and density estimation. Pattern Recognit. Lett. 107, 3–16 (2018). https://doi.org/10.1016/J.PATREC.2017.07.007
3. Porikli, F., et al.: Video surveillance: Past, present, and now the future. IEEE Signal Process. Mag. 30(3), 190–198 (2013). https://doi.org/10.1109/MSP.2013.2241312
4. Elharrouss, O., Almaadeed, N., Al-Maadeed, S.: A review of video surveillance systems. J. Vis. Commun. Image Represent. 77, 103116 (2021). https://doi.org/10.1016/J.JVCIR.2021.103116
5. Tzelepi, M., Tefas, A.: Human crowd detection for drone flight safety using convolutional neural networks.In: 25th Eur. Signal Process. Conf. EUSIPCO 2017, vol 2017-Janua, pp. 743–747 (2017). https://doi.org/10.23919/EUSIPCO.2017.8081306
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