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Deep Open Space Segmentation using Automotive Radar

18 March 2020
F. Nowruzi
Dhanvin Kolhatkar
Prince Kapoor
Fahed Al Hassanat
E. J. Heravi
R. Laganière
Julien Rebut
Waqas Malik
ArXiv (abs)PDFHTML
Abstract

In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.

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