Learning Spatio-Temporal Features via 3D CNNs to Forecast Time-to-Accident

Taif Anjum, Louis Chirade, Beiyu Lin, Apurva Narayan. Learning Spatio-Temporal Features via 3D CNNs to Forecast Time-to-Accident. In Ana Paula Rocha 0001, Luc Steels, H. Jaap van den Herik, editors, Proceedings of the 15th International Conference on Agents and Artificial Intelligence, ICAART 2023, Volume 3, Lisbon, Portugal, February 22-24, 2023. pages 532-540, SCITEPRESS, 2023. [doi]

@inproceedings{AnjumCLN23,
  title = {Learning Spatio-Temporal Features via 3D CNNs to Forecast Time-to-Accident},
  author = {Taif Anjum and Louis Chirade and Beiyu Lin and Apurva Narayan},
  year = {2023},
  doi = {10.5220/0011697900003393},
  url = {https://doi.org/10.5220/0011697900003393},
  researchr = {https://researchr.org/publication/AnjumCLN23},
  cites = {0},
  citedby = {0},
  pages = {532-540},
  booktitle = {Proceedings of the 15th International Conference on Agents and Artificial Intelligence, ICAART 2023, Volume 3, Lisbon, Portugal, February 22-24, 2023},
  editor = {Ana Paula Rocha 0001 and Luc Steels and H. Jaap van den Herik},
  publisher = {SCITEPRESS},
  isbn = {978-989-758-623-1},
}