A novel weakly-supervised approach for RGB-D-based nuclear waste object detection

Sun, L. orcid.org/0000-0002-0393-8665, Zhao, C., Yan, Z. et al. (3 more authors) (2019) A novel weakly-supervised approach for RGB-D-based nuclear waste object detection. IEEE Sensors Journal, 19 (9). pp. 3487-3500. ISSN 1530-437X



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Keywords: Nuclear waste detection and categorization; nuclear waste decommissioning; autonomous waste sorting and segregation
  • Accepted: 27 November 2018
  • Published (online): 19 December 2018
  • Published: 1 May 2019
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: 15 Jan 2020 16:30
Last Modified: 15 Jan 2020 16:35
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/jsen.2018.2888815
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