OccuSpace: Towards a Robust Occupancy Prediction System for Activity Based Workplace. Rahaman, M. S., Pare, H., Liono, J., Salim, F. D., Ren, Y., Chan, J., Kudo, S., Rawling, T., & Sinickas, A. In IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, Kyoto, Japan, March 11-15, 2019, pages 415–418, 2019. IEEE.
Paper doi bibtex @inproceedings{DBLP:conf/percom/RahamanPLSRCKRS19,
author = {Mohammad Saiedur Rahaman and
Harsh Pare and
Jonathan Liono and
Flora D. Salim and
Yongli Ren and
Jeffrey Chan and
Shaw Kudo and
Tim Rawling and
Alex Sinickas},
title = {OccuSpace: Towards a Robust Occupancy Prediction System for Activity
Based Workplace},
booktitle = {{IEEE} International Conference on Pervasive Computing and Communications
Workshops, PerCom Workshops 2019, Kyoto, Japan, March 11-15, 2019},
pages = {415--418},
publisher = {{IEEE}},
year = {2019},
url = {https://doi.org/10.1109/PERCOMW.2019.8730762},
doi = {10.1109/PERCOMW.2019.8730762},
timestamp = {Fri, 27 Dec 2019 00:00:00 +0100},
biburl = {https://dblp.org/rec/conf/percom/RahamanPLSRCKRS19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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