A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction.
Bardh Prenkaj|Paola Velardi|Damiano Distante|Stefano Faralli
| Anthology ID: | DBLP:conf/cikm/PrenkajVD020 |
|---|---|
| Volume: | CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020 |
| Year: | 2020 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 2169-2172 |
| URL: | https://doi.org/10.1145/3340531.3412088 |
| DOI: | https://doi.org/10.1145/3340531.3412088 |
| DBLP: | conf/cikm/PrenkajVD020 |
| BibTeX: |
@inproceedings{prenkaj-2020-reproducibility,
author = {Bardh Prenkaj and
Paola Velardi and
Damiano Distante and
Stefano Faralli},
editor = {Mathieu d'Aquin and
Stefan Dietze and
Claudia Hauff and
Edward Curry and
Philippe Cudr\'{e}-Mauroux},
title = {{A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction}},
booktitle = {{CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020}},
pages = {2169--2172},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3340531.3412088},
doi = {https://doi.org/10.1145/3340531.3412088}
}