Controllable model compression for roadside camera depth estimation

Ople, J.J.M., Chen, S.-F., Chen, Y.-Y. et al. (4 more authors) (2022) Controllable model compression for roadside camera depth estimation. IEEE Transactions on Intelligent Transportation Systems. ISSN 1524-9050

Abstract

Metadata

Authors/Creators:
  • Ople, J.J.M.
  • Chen, S.-F.
  • Chen, Y.-Y.
  • Hua, K.-L.
  • Hijji, M.
  • Yang, P.
  • Muhammad, K.
Copyright, Publisher and Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Smart sensors; neural network compression; depth estimation; genetic algorithm; sustainable solutions; intelligent transportation systems
Dates:
  • Accepted: 6 April 2022
  • Published (online): 13 May 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 16 May 2022 11:24
Last Modified: 16 May 2022 11:24
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/tits.2022.3166873

Download

Accepted Version


Embargoed until: 13 May 2023

Filename: FINAL VERSION.pdf

Request a copy

file not available

Share / Export

Statistics