Kevin Smith
Kevin Smith
Associate Professor, KTH Royal Institute of Technology & Science for Life Laboratory
Verified email at kth.se - Homepage
Title
Cited by
Cited by
Year
SLIC superpixels compared to state-of-the-art superpixel methods
R Achanta, A Shaji, K Smith, A Lucchi, P Fua, S Süsstrunk
IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (11), 2274 …, 2012
7430*2012
Using particles to track varying numbers of interacting people
K Smith, D Gatica-Perez, JM Odobez
Computer Vision and Pattern Recognition (CVPR) 1, 962-969, 2005
2752005
Supervoxel-based segmentation of mitochondria in EM image stacks with learned shape features
A Lucchi, K Smith, R Achanta, G Knott, P Fua
IEEE Transactions on Medical Imaging 31 (2), 474-486, 2012
2472012
Evaluating multi-object tracking
K Smith, D Gatica-Perez, JM Odobez, S Ba
Computer Vision and Pattern Recognition (CVPR)-Workshops, 36-36, 2005
1942005
Tracking the visual focus of attention for a varying number of wandering people
K Smith, SO Ba, JM Odobez, D Gatica-Perez
IEEE transactions on pattern analysis and machine intelligence 30 (7), 1212-1229, 2008
1532008
Detecting abandoned luggage items in a public space
K Smith, P Quelhas, D Gatica-Perez
Computer Vision and Pattern Recognition (CVPR)-Workshops, 2006
1242006
A fully automated approach to segmentation of irregularly shaped cellular structures in EM images
A Lucchi, K Smith, R Achanta, V Lepetit, P Fua
MICCAI - International Conference on Medical Image Computing and Computer …, 2010
1212010
Digital image analysis in breast pathology – from image processing techniques to artificial intelligence
S Robertson, H Azizpour, K Smith, J Hartman
Translational Research 194, 19-35, 2018
1032018
General Constraints for Batch Multiple-Target Tracking Applied to Large-Scale Videomicroscopy
K Smith, V Lepetit, A Carleton
Computer Vision and Pattern Recognition (CVPR), 2008
93*2008
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
M Teye, H Azizpour, K Smith
International Conference on Machine Learning (ICML), 2018
872018
CIDRE: an illumination-correction method for optical microscopy
K Smith, Y Li, F Piccinini, G Csucs, C Balazs, A Bevilacqua, P Horvath
Nature Methods 12 (5), 404-406, 2015
822015
Fast ray features for learning irregular shapes
K Smith, A Carleton, V Lepetit
Computer Vision and Pattern Recognition (CVPR), 397-404, 2009
752009
Deep learning is combined with massive-scale citizen science to improve large-scale image classification
DP Sullivan, CF Winsnes, L Ĺkesson, M Hjelmare, M Wiking, R Schutten, ...
Nature biotechnology 36 (9), 820-828, 2018
742018
Are spatial and global constraints really necessary for segmentation?
A Lucchi, Y Li, X Boix, K Smith, P Fua
International Conference on Computer Vision (ICCV), 9-16, 2011
722011
Slic superpixels
A Radhakrishna, A Shaji, K Smith, A Lucchi, P Fua, S Susstrunk
Dept. School Comput. Commun. Sci., EPFL, Lausanne, Switzerland, Tech. Rep 149300, 2010
702010
Structured image segmentation using kernelized features
A Lucchi, Y Li, K Smith, P Fua
European Conference on Computer Vision (ECCV), 400-413, 2012
692012
Intelligent image-based in situ single-cell isolation
C Brasko, K Smith, C Molnar, N Farago, L Hegedus, A Balind, T Balassa, ...
Nature communications 9 (1), 1-7, 2018
382018
Bayesian methods for visual multi-object tracking with applications to human activity recognition
K Smith
École Polytechnique Fédérale de Lausanne, 2007
372007
Advanced cell classifier: user-friendly machine-learning-based software for discovering phenotypes in high-content imaging data
F Piccinini, T Balassa, A Szkalisity, C Molnar, L Paavolainen, K Kujala, ...
Cell systems 4 (6), 651-655. e5, 2017
352017
Order matters: A distributed sampling method for multiple-object tracking
K Smith, D Gatica-perez
Proc. British Machine Vision Conference (BMVC), 2004
35*2004
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Articles 1–20