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A robust rule-based ensemble framework using mean-shift segmentation for hyperspectral image classification

Roodposhti, Majid Shadman, Lucieer, Arko, Anees, Asim and Bryan, Brett A. 2019, A robust rule-based ensemble framework using mean-shift segmentation for hyperspectral image classification, Remote Sensing, vol. 11, no. 17, pp. 1-20, doi: 10.3390/rs11172057.

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Title A robust rule-based ensemble framework using mean-shift segmentation for hyperspectral image classification
Author(s) Roodposhti, Majid Shadman
Lucieer, Arko
Anees, Asim
Bryan, Brett A.ORCID iD for Bryan, Brett A. orcid.org/0000-0003-4834-5641
Journal name Remote Sensing
Volume number 11
Issue number 17
Article ID 2057
Start page 1
End page 20
Total pages 20
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2019
ISSN 2072-4292
Keyword(s) image classification
ensemble
mean-shift
entropy
uncertainty map
Language eng
DOI 10.3390/rs11172057
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30130020

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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.