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Conference item

Distant vehicle detection using radar and vision

Alternative title:
Conference paper
Abstract:

For autonomous vehicles to be able to operate successfully they need to be aware of other vehicles with sufficient time to make safe, stable plans. Given the possible closing speeds between two vehicles, this necessitates the ability to accurately detect distant vehicles. Many current image-based object detectors using convolutional neural networks exhibit excellent performance on existing datasets such as KITTI. However, the performance of these networks falls when detecting small (distant) ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ICRA.2019.8794312

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
St Peter's College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Keble College
Role:
Author
ORCID:
0000-0001-6562-8454
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Name:
Engineering & Physical Sciences Research Council
Grant:
EP/M019918/1
Publisher:
Institute of Electrical and Electronics Engineers
Host title:
2019 IEEE International Conference on Robotics and Automation (ICRA)
Journal:
2019 IEEE International Conference on Robotics and Automation (ICRA) More from this journal
Pages:
8311-8317
Publication date:
2019-08-12
Acceptance date:
2019-01-31
DOI:
EISSN:
2577-087X
ISSN:
1050-4729
Keywords:
Pubs id:
pubs:1026223
UUID:
uuid:0bb1a1d5-21ab-4bd3-9402-8a3c394bd236
Local pid:
pubs:1026223
Source identifiers:
1026223
Deposit date:
2019-07-03

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