Kaiqun Fu, Taoran Ji, Liang Zhao, Chang-Tien Lu. TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction. In Farnoush Banaei Kashani, Goce Trajcevski, Ralf Hartmut Güting, Lars Kulik, Shawn D. Newsam, editors, Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2019, Chicago, IL, USA, November 5-8, 2019. pages 329-338, ACM, 2019. [doi]
@inproceedings{FuJZL19,
title = {TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction},
author = {Kaiqun Fu and Taoran Ji and Liang Zhao and Chang-Tien Lu},
year = {2019},
doi = {10.1145/3347146.3359381},
url = {https://doi.org/10.1145/3347146.3359381},
researchr = {https://researchr.org/publication/FuJZL19},
cites = {0},
citedby = {0},
pages = {329-338},
booktitle = {Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2019, Chicago, IL, USA, November 5-8, 2019},
editor = {Farnoush Banaei Kashani and Goce Trajcevski and Ralf Hartmut Güting and Lars Kulik and Shawn D. Newsam},
publisher = {ACM},
isbn = {978-1-4503-6909-1},
}