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Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework

Date

2020
Proceedings Paper
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dc.contributor.authorSóñora-Mengana, Alexander
dc.contributor.authorGonidakis, Panagiotis
dc.contributor.authorJansen, Bart
dc.contributor.authorGarcia-Naranjo, Juan
dc.contributor.authorVandemeulebroucke, Jef
dc.contributor.imecauthorJansen, Bart
dc.contributor.imecauthorVandemeulebroucke, Jef
dc.contributor.orcidimecJansen, Bart::0000-0001-8042-6834
dc.contributor.orcidimecVandemeulebroucke, Jef::0000-0001-5714-3254
dc.date.accessioned2021-10-29T04:36:00Z
dc.date.available2021-10-29T04:36:00Z
dc.date.embargo9999-12-31
dc.date.issued2020
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/35993
dc.identifier.urlhttps://doi.org/10.1117/12.2549778
dc.source.beginpage113143T
dc.source.conferenceMedical Imaging 2020: Computer-Aided Diagnosis
dc.source.conferencedate15/02/2020
dc.source.conferencelocationHouston, TX USA
dc.title

Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework

dc.typeProceedings paper
dspace.entity.typePublication
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