Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories-Reference-Cited by-同舟云学术

Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

He Songtao¹,Sadeghi Mohammad Amin²,Chawla Sanjay²,Alizadeh Mohammad¹,Balakrishnan Hari¹,Madden Samuel¹

Affiliation:

1. MIT CSAIL

2. HBKU QCRI

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710843.pdf?arnumber=9710843

Reference31 articles.

1. Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective

2. Deep sets;zaheer;arXiv preprint arXiv 1703 06870,2017

3. SDCAE: Stack Denoising Convolutional Autoencoder Model for Accident Risk Prediction Via Traffic Big Data

4. Learning deep representation from big and heterogeneous data for traffic accident inference;chen;Proceedings of the AAAI Conference on Artificial Intelligence,2016

5. OpenStreetMap: User-Generated Street Maps

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