Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction

Holder, C.; Breckon, T.P.

doi:10.1109/IVS.2018.8500526

Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction

Holder, C.; Breckon, T.P.

Authors

C. Holder

Professor Toby Breckon toby.breckon@durham.ac.uk
Professor

Citation

Holder, C., & Breckon, T. (2018, June). Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction. Presented at The 29th Intelligent Vehicles Symposium (IEEE IV 2018)., Changshu, China

Presentation Conference Type	Conference Paper (published)
Conference Name	The 29th Intelligent Vehicles Symposium (IEEE IV 2018).
Start Date	Jun 26, 2018
End Date	Jun 29, 2018
Acceptance Date	Apr 16, 2018
Publication Date	2018
Deposit Date	May 4, 2018
Publicly Available Date	May 8, 2018
Publisher	Institute of Electrical and Electronics Engineers
Pages	2104-2110
Book Title	Proc. Intelligent Vehicles Symposium
DOI	https://doi.org/10.1109/IVS.2018.8500526
Keywords	end-to-end autonomous driving, off-road autonomous vehicles, stereo visual odometry, path prediction, steering control
Public URL	https://durham-repository.worktribe.com/output/1145549
Publisher URL	http://www.2018iv.org/

Files

Accepted Conference Proceeding (1.1 Mb)
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