Controllable model compression for roadside camera depth estimation

Ople, J.J.M., Chen, S.-F., Chen, Y.-Y. et al. (4 more authors) (2023) Controllable model compression for roadside camera depth estimation. IEEE Transactions on Intelligent Transportation Systems, 24 (12). pp. 15478-15485. ISSN 1524-9050

Abstract

Metadata

Item Type: Article
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:
  • Published: December 2023
  • Published (online): 13 May 2022
  • Accepted: 6 April 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: 10 Jul 2024 11:16
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/tits.2022.3166873
Open Archives Initiative ID (OAI ID):

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