Book Chapter2027

Human Anomalous Activity Detection System Based On Infrared Grid Sensor

Ololade Babatunde, Raqibul Hasan

Proceedings of Innovative Computing 2026 Vol 4-Emerging Topics in Future Internet

Springer Nature Singapore, pp. 75-81, ISBN: 9789819207787

Keywords

  • semi-supervised anomaly detection
  • autoencoder reconstruction error
  • K-means clustering

CCDS Authors

Raqibul Hasan, PhD
Raqibul Hasan, PhD

Raqibul Hasan, PhD

  • Director, NEST & IPT Wings
  • Assistant Professor

    Department of Computer Science and Engineering

    Independent University, Bangladesh (IUB)

References

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  2. 2.Mahmudul Hasan, Jonghyun Choi, Jan Neumann, Amit K. Roy-Chowdhury, Larry S. Davis. (2016). Learning Temporal Regularity in Video Sequences. IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings, 733–742[10.1109/cvpr.2016.86]
  3. 3.Markos Markou, Sameer Singh. (2003). Novelty detection: a review—part 1: statistical approaches. Signal Processing, 83(12), 2481–2497[10.1016/j.sigpro.2003.07.018]
  4. 4.Mariana-Iuliana Georgescu, Antonio Barbalau, Radu Tudor Ionescu, Fahad Shahbaz Khan, Marius Popescu, Mubarak Shah. (2021). Anomaly Detection in Video via Self-Supervised and Multi-Task Learning. IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings, 12737–12747[10.1109/cvpr46437.2021.01255]
  5. 5.Muhammad Fahim, Alberto Sillitti. (2019). Anomaly Detection, Analysis and Prediction Techniques in IoT Environment: A Systematic Literature Review. IEEE Access, 7, 81664–81681[10.1109/access.2019.2921912]