Raphael Sznitman
Cited by
Cited by
Learning active learning from data
K Konyushkova, R Sznitman, P Fua
Conference on Neural Information Processing Systems (NIPS), 2017
Surgical data science–from concepts toward clinical translation
L Maier-Hein, M Eisenmann, D Sarikaya, K März, T Collins, A Malpani, ...
Medical image analysis 76, 102306, 2022
Articulated multi-instrument 2-D pose estimation using fully convolutional networks
X Du, T Kurmann, PL Chang, M Allan, S Ourselin, R Sznitman, JD Kelly, ...
IEEE transactions on medical imaging 37 (5), 1276-1287, 2018
Twenty questions with noise: Bayes optimal policies for entropy loss
B Jedynak, PI Frazier, R Sznitman
Journal of Applied Probability 49 (1), 114-136, 2012
Stereo correspondence and reconstruction of endoscopic data challenge
M Allan, J Mcleod, C Wang, JC Rosenthal, Z Hu, N Gard, P Eisert, KX Fu, ...
arXiv preprint arXiv:2101.01133, 2021
Simultaneous recognition and pose estimation of instruments in minimally invasive surgery
T Kurmann, P Marquez Neila, X Du, P Fua, D Stoyanov, S Wolf, ...
Medical Image Computing and Computer-Assisted Intervention− MICCAI 2017 …, 2017
Propulsive force measurements and flow behavior of undulatory swimmers at low Reynolds number
J Sznitman, X Shen, R Sznitman, PE Arratia
Physics of Fluids 22 (12), 2010
Pathological OCT retinal layer segmentation using branch residual U-shape networks
S Apostolopoulos, S De Zanet, C Ciller, S Wolf, R Sznitman
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
Data-driven visual tracking in retinal microsurgery
R Sznitman, K Ali, R Richa, RH Taylor, GD Hager, P Fua
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th …, 2012
Active testing for face detection and localization
R Sznitman, B Jedynak
IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (10), 1914 …, 2010
Quantitative analysis of mouse retinal layers using automated segmentation of spectral domain optical coherence tomography images
C Dysli, V Enzmann, R Sznitman, MS Zinkernagel
Translational vision science & technology 4 (4), 9-9, 2015
Visual tracking using the sum of conditional variance
R Richa, R Sznitman, R Taylor, G Hager
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011
Introducing geometry in active learning for image segmentation
K Konyushkova, R Sznitman, P Fua
Proceedings of the IEEE International Conference on Computer Vision, 2974-2982, 2015
Supervised machine learning for analysing spectra of exoplanetary atmospheres
P Márquez-Neila, C Fisher, R Sznitman, K Heng
Nature astronomy 2 (9), 719-724, 2018
Fast Part-Based Classification for Instrument Detection in Minimally Invasive Surgery
R Sznitman, C Becker, P Fua
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 …, 2014
Unified detection and tracking of instruments during retinal microsurgery
R Sznitman, R Richa, RH Taylor, B Jedynak, GD Hager
IEEE transactions on pattern analysis and machine intelligence 35 (5), 1263-1273, 2012
A deep learning approach to automatic detection of early glaucoma from visual fields
ŞS Kucur, G Hollo, R Sznitman
PloS one 13 (11), e0206081, 2018
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
S Bodenstedt, M Allan, A Agustinos, X Du, L Garcia-Peraza-Herrera, ...
arXiv preprint arXiv:1805.02475, 2018
Visual tracking of surgical tools for proximity detection in retinal surgery
R Richa, M Balicki, E Meisner, R Sznitman, R Taylor, G Hager
Information Processing in Computer-Assisted Interventions: Second …, 2011
Vision-based proximity detection in retinal surgery
R Richa, M Balicki, R Sznitman, E Meisner, R Taylor, G Hager
IEEE Transactions on Biomedical Engineering 59 (8), 2291-2301, 2012
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