Imbalanced Learning for Robust Moving Object Classification in Video Surveillance Applications

Rania Rebai Boukhriss, Ikram Chaabane, Radhouane Guermazi, Emna Fendri, Mohamed Hammami. Imbalanced Learning for Robust Moving Object Classification in Video Surveillance Applications. In Ajith Abraham, Niketa Gandhi, Thomas Hanne, Tzung-Pei Hong, Tatiane Nogueira Rios, Weiping Ding 0001, editors, Intelligent Systems Design and Applications - 21st International Conference on Intelligent Systems Design and Applications (ISDA 2021) Held During December 13-15, 2021. Volume 418 of Lecture Notes in Networks and Systems, pages 199-209, Springer, 2021. [doi]

@inproceedings{BoukhrissCGFH21,
  title = {Imbalanced Learning for Robust Moving Object Classification in Video Surveillance Applications},
  author = {Rania Rebai Boukhriss and Ikram Chaabane and Radhouane Guermazi and Emna Fendri and Mohamed Hammami},
  year = {2021},
  doi = {10.1007/978-3-030-96308-8_18},
  url = {https://doi.org/10.1007/978-3-030-96308-8_18},
  researchr = {https://researchr.org/publication/BoukhrissCGFH21},
  cites = {0},
  citedby = {0},
  pages = {199-209},
  booktitle = {Intelligent Systems Design and Applications - 21st International Conference on Intelligent Systems Design and Applications (ISDA 2021) Held During December 13-15, 2021},
  editor = {Ajith Abraham and Niketa Gandhi and Thomas Hanne and Tzung-Pei Hong and Tatiane Nogueira Rios and Weiping Ding 0001},
  volume = {418},
  series = {Lecture Notes in Networks and Systems},
  publisher = {Springer},
  isbn = {978-3-030-96308-8},
}