Random forest dissimilarity based multi-view learning for Radiomics application

Hongliu Cao, Simon Bernard, Robert Sabourin, Laurent Heutte

DOI: 10.1016/j.patcog.2018.11.011
Published: 2019-04
Container: Pattern Recognition
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1016/j.patcog.2018.11.011,
  title = {Random forest dissimilarity based multi-view learning for Radiomics application},
  author = {Hongliu Cao and Simon Bernard and Robert Sabourin and Laurent Heutte},
  year = {2019},
  journal = {Pattern Recognition},
  doi = {10.1016/j.patcog.2018.11.011},
  url = {https://doi.org/10.1016/j.patcog.2018.11.011}
}

RIS

TY  - JOUR
TI  - Random forest dissimilarity based multi-view learning for Radiomics application
AU  - Hongliu Cao
AU  - Simon Bernard
AU  - Robert Sabourin
AU  - Laurent Heutte
PY  - 2019
JO  - Pattern Recognition
DO  - 10.1016/j.patcog.2018.11.011
UR  - https://doi.org/10.1016/j.patcog.2018.11.011
ER  -

APA

Cao, H., Bernard, S., Sabourin, R., & Heutte, L. (2019). Random forest dissimilarity based multi-view learning for Radiomics application. Pattern Recognition. https://doi.org/10.1016/j.patcog.2018.11.011

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hal · retrieved 2026-09-25T21:56:25.217Z