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RING-Net : road inference from GPS trajectories using a ..:

, In: Proceedings of the 10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data,

Eftelioglu, Emre ; Garg, Ravi ; Kango, Vaibhav.. - p. 17-26 , 2022

Link: https://dl.acm.org/doi/10.1145/3557917.3567617

RT 
T1 <cTitle>Proceedings of the 10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data</cTitle>: T1 <Title>RING-Net				: road inference from GPS trajectories using a deep segmentation network</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3567617&Exemplar=1&LAN=DE
				
A1 Eftelioglu, Emre
A1 Garg, Ravi
A1 Kango, Vaibhav
A1 Gohil, Chintan
A1 Chowdhury, Amber Roy
PB ACM
YR 2022
K1 GPS trajectories
K1 deep learning
K1 road inference
K1 segmentation
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by regression
K1 Information systems
K1 Information systems applications
K1 Spatial-temporal systems
K1 Global positioning systems
K1 Applied computing
K1 Operations research
K1 Transportation
K1 Geographic information systems
K1 Artificial intelligence
K1 Computer vision
K1 Computer vision problems
K1 Image segmentation
SP 17
OP 26
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3557917.3567617
DO https://dl.acm.org/doi/10.1145/3557917.3567617
SF ELIB - SuUB Bremen

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