1 code implementation • 21 Mar 2024 • Wei Chen, Yuxuan Liang, Yuanshao Zhu, Yanchuan Chang, Kang Luo, Haomin Wen, Lei LI, Yanwei Yu, Qingsong Wen, Chao Chen, Kai Zheng, Yunjun Gao, Xiaofang Zhou, Yu Zheng
In this paper, we present a comprehensive review of the development and recent advances in deep learning for trajectory computing (DL4Traj).
1 code implementation • 19 Jan 2024 • Xinyu Su, Jianzhong Qi, Egemen Tanin, Yanchuan Chang, Majid Sarvi
Our key insight is to learn from the locations that resemble those in the region of interest, and we propose a selective masking strategy to enable the learning.
1 code implementation • 7 Dec 2023 • Fengze Sun, Jianzhong Qi, Yanchuan Chang, Xiaoliang Fan, Shanika Karunasekera, Egemen Tanin
Our model is powered by a dual-feature attentive fusion module named DAFusion, which fuses embeddings from different region features to learn higher-order correlations between the regions as well as between the different types of region features.
1 code implementation • 11 Oct 2022 • Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin
Trajectory similarity measures act as query predicates in trajectory databases, making them the key player in determining the query results.