Veronika Cheplygina

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David TaxAssistant professor, Delft University of TechnologyVerified email at tudelft.nl
Marco LoogDelft University of Technology & University of CopenhagenVerified email at tudelft.nl
Marleen de BruijneProfessor of AI in Medical Image Analysis; Erasmus MC Rotterdam and University of CopenhagenVerified email at diku.dk
Josien PluimProfessor of Medical Image Analysis, Eindhoven University of Technology / UMC UtrechtVerified email at tue.nl
Eric GrangerProfessor, Dept. of Systems Engineering, École de technologie supérieure, LIVIA, REPARTIVerified email at etsmtl.ca
Lauge SørensenAssociate Professor at University of Copenhagen, Senior Researcher at Biomediq A/S and Cerebriu A/SVerified email at diku.dk
Marc-André CarbonneauUbisoft La ForgeVerified email at ubisoft.com
Robert P.W. DuinDelft University of TechnologyVerified email at tudelft.nl
Silas ØrtingPost Doc, Computer Science, University of CopenhagenVerified email at di.ku.dk
Jesper Holst PedersenOverlæge, dr.medVerified email at regionh.dk
Diana MateusEcole Centrale NantesVerified email at ec-nantes.fr
Adria Perez-RoviraDaon IncVerified email at daon.com
Yenisel Plasencia CalañaMaastricht UniversityVerified email at maastrichtuniversity.nl
Ethem AlpaydinProfessor of Computer Engineering, Ozyegin University, IstanbulVerified email at ozyegin.edu.tr
Jens PetersenComputer Science, University of CopenhagenVerified email at diku.dk
Mathilde Marie Winkler WilleSpeciallæge i radiologi, ph.d. Nordsjællands HospitalVerified email at regionh.dk
Lena Maier-HeinProfessor, German Cancer Research CenterVerified email at dkfz.de
Oana InelDelft University of TechnologyVerified email at tudelft.nl
Andrew DoyleMcGill UniversityVerified email at mail.mcgill.ca
Arno van HiltenPhD Candidate, Erasmus MCVerified email at erasmusmc.nl

Veronika Cheplygina

IT University Copenhagen

Verified email at itu.dk - Homepage

pattern recognition machine learning medical imaging open science failure


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Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis V Cheplygina, M de Bruijne, JPW Pluim Medical image analysis 54, 280-296, 2019	274	2019
Multiple instance learning: A survey of problem characteristics and applications MA Carbonneau, V Cheplygina, E Granger, G Gagnon Pattern Recognition 77, 329-353, 2018	240	2018
Multiple instance learning with bag dissimilarities V Cheplygina, DMJ Tax, M Loog Pattern recognition 48 (1), 264-275, 2015	94	2015
Dissimilarity-based Ensembles for Multiple Instance Learning V Cheplygina, DMJ Tax, M Loog Transactions on Neural Networks and Learning Systems 27 (6), 1379 - 1391, 2016	47	2016
Single-vs. multiple-instance classification E Alpaydın, V Cheplygina, M Loog, DMJ Tax Pattern recognition 48 (9), 2831-2838, 2015	41	2015
Transfer learning for multi-center classification of chronic obstructive pulmonary disease V Cheplygina, IP Pena, JH Pedersen, DA Lynch, L Sørensen, ... Journal of Biomedical and Health Informatics 22 (5), 1486 - 1496, 2018	40	2018
On classification with bags, groups and sets V Cheplygina, DMJ Tax, M Loog Pattern recognition letters 59, 11-17, 2015	38	2015
Classification of COPD with Multiple Instance Learning V Cheplygina, L Sørensen, D Tax, JH Pedersen, M Loog, M de Bruijne International Conference on Pattern Recognition, 1508-1513, 2014	36	2014
Pruned random subspace method for one-class classifiers V Cheplygina, DMJ Tax International Workshop on Multiple Classifier Systems, 96-105, 2011	35	2011
Bag dissimilarities for multiple instance learning DMJ Tax, M Loog, RPW Duin, V Cheplygina, WJ Lee International Workshop on Similarity-Based Pattern Recognition, 222-234, 2011	29	2011
Cats or CAT scans: Transfer learning from natural or medical image source data sets? V Cheplygina Current Opinion in Biomedical Engineering 9, 21-27, 2019	28	2019
A survey of crowdsourcing in medical image analysis S Ørting, A Doyle, A van Hilten, M Hirth, O Inel, CR Madan, P Mavridis, ... arXiv preprint arXiv:1902.09159, 2019	26	2019
Early experiences with crowdsourcing airway annotations in chest CT V Cheplygina, A Perez-Rovira, W Kuo, HAWM Tiddens, M De Bruijne Deep Learning and Data Labeling for Medical Applications, 209-218, 2016	24	2016
Ten simple rules for getting started on Twitter as a scientist V Cheplygina, F Hermans, C Albers, N Bielczyk, I Smeets PLoS computational biology 16 (2), e1007513, 2020	20	2020
Label Stability in Multiple Instance Learning V Cheplygina, L Sørensen, DMJ Tax, M de Bruijne, M Loog Medical Image Computing and Computer Assisted Interventions, 539-546, 2015	20	2015
Bridging structure and feature representations in graph matching WJ Lee, V Cheplygina, DMJ Tax, M Loog, RPW Duin International Journal of Pattern Recognition and Artificial Intelligence 26 (05), 2012	13	2012
Crowd disagreement about medical images is informative V Cheplygina, JPW Pluim arXiv preprint arXiv:1806.08174, 2018	12	2018
On the informativeness of asymmetric dissimilarities Y Plasencia-Calaña, V Cheplygina, RPW Duin, EB García-Reyes, ... International Workshop on Similarity-Based Pattern Recognition, 75-89, 2013	12	2013
Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images IP Pena, V Cheplygina, S Paschaloudi, M Vuust, J Carl, UM Weinreich, ... PLoS ONE 13 (10), e0205397, 2018	11	2018
MIL, A Matlab Toolbox for Multiple Instance Learning DMJ Tax, V Cheplygina http://prlab.tudelft.nl/david-tax/mil.html, 2015	10*	2015

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