Evaluating architecture impacts on deep imitation learning performance for autonomous driving

Kebria, Parham M, Alizadehsani, Roohallah, Salaken, Syed Moshfeq, Hossain, Ibrahim, Khosravi, Abbas, Kabir, Dipu, Koohestani, Afsaneh, Asadi, Houshyar, Nahavandi, Saeid, Tunsel, Edward and Saif, Mehrdad 2019, Evaluating architecture impacts on deep imitation learning performance for autonomous driving, in ICIT 2019 : Proceedings of the 2019 20th IEEE International Conference on Industrial Technology, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 865-870, doi: 10.1109/icit.2019.8755084.

Attached Files
Name Description MIMEType Size Downloads

Title Evaluating architecture impacts on deep imitation learning performance for autonomous driving
Author(s) Kebria, Parham M
Alizadehsani, Roohallah
Salaken, Syed MoshfeqORCID iD for Salaken, Syed Moshfeq orcid.org/0000-0001-8632-2665
Hossain, Ibrahim
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Kabir, Dipu
Koohestani, Afsaneh
Asadi, HoushyarORCID iD for Asadi, Houshyar orcid.org/0000-0002-3620-8693
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Tunsel, Edward
Saif, Mehrdad
Conference name IEEE Industrial Electronics Society. Conference (20th : 2019 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 2019/02/13 - 2019/02/15
Title of proceedings ICIT 2019 : Proceedings of the 2019 20th IEEE International Conference on Industrial Technology
Editor(s) [Unknown]
Publication date 2019
Series IEEE Industrial Electronics Society Conference
Start page 865
End page 870
Total pages 6
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Keyword(s) Autonomous systems
Autonomous driving
Deep learning
Imitation learning
Simulation
Language eng
DOI 10.1109/icit.2019.8755084
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2019, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30126465

Document type: Conference Paper
Collections: Centre for Intelligent Systems Research
GTP Research
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 19 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Wed, 17 Jul 2019, 10:20:45 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.