Benchmarking Jetson Edge Devices with an End-to-End Video-Based Anomaly Detection System

Author:

Pham Hoang V.,Tran Thinh G.,Le Chuong D.,Le An D.,Vo Hien B.

Publisher

Springer Nature Switzerland

Reference20 articles.

1. Tian, Y., Pang, G., Chen, Y., Singh, R., Verjans, J.W., Carneiro, G.: Weakly-supervised video anomaly detection with robust temporal feature magnitude learning. In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC, Canada, pp. 4955–4966 (2021). https://doi.org/10.1109/ICCV48922.2021.00493

2. Haoqi, F., Yanghao, L., Bo, X., Wan-Yen, L., Christoph, F.: PySlowfast (2020). https://github.com/facebookresearch/slowfast

3. NVIDIA: Torch-TensorRT, 08 April 2020. https://github.com/NVIDIA/TensorRT

4. Mayur, R., Parate, K.M., Bhurchandi, A.K.: Anomaly detection in residential video surveillance on edge devices in IoT framework, July 2021

5. Piciarelli, C., Micheloni, C., Foresti, G.L.: Trajectory-based anomalous event detection. IEEE Trans. Circuits Syst. Video Technol. 18(11), 1544–1554 (2008). https://doi.org/10.1109/TCSVT.2008.2005599

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