Discovery of stay area in indoor trajectories of moving objects

Author:

Zhou Yang,Chen Yi,Pi Dechang

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference27 articles.

1. A method to evaluate haptic interfaces for working dogs;Byrne;International Journal of Human - Computer Studies,2017

2. An indoor trajectory frequent pattern mining algorithm based on vague grid sequence;Chen;Expert Systems with Applications,2019

3. Research on Spatio-temporal Clustering Algorithm for Trajectory Staying Point Extraction of Mobile Smartphone Users;Cui;Journal of Southwest China Normal University (Natural Science Edition),2016

4. Dai, C., Pi, D., Becker, S. I., etc. al. (2020). CenEEGs: Valid EEG Selection for Classification. ACM Transactions on Knowledge Discovery from Data,14(2):1-25, 2020. DOI:org/10.1145/3371153.

5. Dai, C., Wu, J., Pi, D., etc.al. (2020). Brain EEG Time Series Clustering Using Maximum Weight Clique. IEEE Transactions on Cybernetics. DOI:10.1109/TCYB.2020.2974776.

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1. Behavior recognition of non-motorized transport at intersections using dual-channel grid model based on disordered trajectory point data;Physica A: Statistical Mechanics and its Applications;2024-09

2. Indoor Framework;International Journal of Web Services Research;2022-11-25

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