Kalle Åström

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Anders HeydenProfessor in Mathematics, Lund UniversityVerificeret mail på maths.lth.se
Magnus OskarssonAssociate professor of mathematics, Lund UniversityVerificeret mail på math.lth.se
Fredrik KahlProfessor, Chalmers University of TechnologyVerificeret mail på chalmers.se
Martin ByrödLunds universitetVerificeret mail på maths.lth.se
Hakan ArdoLund UniversityVerificeret mail på maths.lth.se
Niels Chr OvergaardLunds UniversitetVerificeret mail på math.lth.se
Ida ArvidssonPostdoctoral Researcher, Centre for Mathematical Sciences, Lund UniversityVerificeret mail på math.lth.se
Viktor LarssonAssistant Professor at Lund UniversityVerificeret mail på math.lth.se
Mikael NilssonLund UniversityVerificeret mail på math.lth.se
Olof EnqvistAssistant Professor, Department of Signals and Systems, Chalmers University of Technology, GöteborgVerificeret mail på chalmers.se
Anders EricssonVerificeret mail på acreo.se
Oleksiy GuzhvaDepartment of Biosystems and Technology, Swedish University of Agricultural SciencesVerificeret mail på slu.se
Fredrik TufvessonProfessor, Lund University, SwedenVerificeret mail på eit.lth.se
Anders BjartellProfessor i UrologiVerificeret mail på med.lu.se
Agnieszka KrzyzanowskaBRIC, copenhagen universityVerificeret mail på bric.ku.dk
Gabrielle FloodPostdoctoral Researcher, Centre for Mathematical Sciences, Lund UniversityVerificeret mail på math.lth.se
Martin LarssonPhD, Centre for Mathematical Sciences, Lund UniversityVerificeret mail på math.lth.se
Zhayida SimayijiangLund universityVerificeret mail på maths.lth.se
Kenneth BatstoneLund UniversityVerificeret mail på math.lth.se
Tomas PajdlaAssociate professor, Czech Technical University in PragueVerificeret mail på cvut.cz

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Kalle Åström

Professor, Centre for Mathematical Sciences, Lund University, Sweden

Verificeret mail på maths.lth.se - Startside

computer vision machine learning structure from sound


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
Revisiting the pnp problem: A fast, general and optimal solution Y Zheng, Y Kuang, S Sugimoto, K Astrom, M Okutomi Proceedings of the IEEE International Conference on Computer Vision, 2344-2351, 2013	462	2013
Euclidean reconstruction from image sequences with varying and unknown focal length and principal point A Heyden, K Astrom Proceedings of IEEE Computer Society Conference on Computer Vision and …, 1997	355	1997
Euclidean reconstruction from constant intrinsic parameters K Åström, A Heyden Int. Conf. Pattern Recognition 1, 339-343, 1996	292*	1996
Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges B Piasecka, D Duffy, A Urrutia, H Quach, E Patin, C Posseme, J Bergstedt, ... Proceedings of the National Academy of Sciences 115 (3), E488-E497, 2018	221	2018
FLIP: A Difference Evaluator for Alternating Images. P Andersson, J Nilsson, T Akenine-Möller, M Oskarsson, K Åström, ... Proc. ACM Comput. Graph. Interact. Tech. 3 (2), 15:1-15:23, 2020	215	2020
Solutions to minimal generalized relative pose problems MO HenrikStewénius, K Aström, D Nistér Proceedings of the Workshop on Omnidirectional Vision, Beijing, China, 2005	177	2005
Efficient solvers for minimal problems by syzygy-based reduction V Larsson, K Astrom, M Oskarsson Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	155	2017
Robust factorization H Aanæs, R Fisker, K Astrom, JM Carstensen IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (9), 1215-1225, 2002	151	2002
Conjugate gradient bundle adjustment M Byröd, K Åström Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010	129	2010
Motion from the frontier of curved surfaces R Cipolla, KE Astrom, PJ Giblin Proceedings of IEEE International Conference on Computer Vision, 269-275, 1995	129	1995
Critical motions for auto-calibration when some intrinsic parameters can vary F Kahl, B Triggs, K Åström Journal of Mathematical Imaging and Vision 13, 131-146, 2000	110	2000
Minimal conditions on intrinsic parameters for euclidean reconstruction A Heyden, K Åström Computer Vision—ACCV'98, 169-176, 1997	103	1997
Fast and stable polynomial equation solving and its application to computer vision M Byröd, K Josephson, K Åström International Journal of Computer Vision 84, 237-256, 2009	102	2009
Generalised epipolar constraints K Åström, R Cipolla, PJ Giblin Computer Vision—ECCV'96: 4th European Conference on Computer Vision …, 1996	93	1996
A complete characterization and solution to the microphone position self-calibration problem Y Kuang, S Burgess, A Torstensson, K Åström 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013	91	2013
Flexible calibration: Minimal cases for auto-calibration A Heyden, K Astrom Proceedings of the Seventh IEEE International Conference on Computer Vision …, 1999	91	1999
Algebraic properties of multilinear constraints A Heyden, K Åström Mathematical Methods in the Applied Sciences 20 (13), 1135-1162, 1997	89	1997
Towards grading gleason score using generically trained deep convolutional neural networks H Källén, J Molin, A Heyden, C Lundström, K Åström 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1163-1167, 2016	88	2016
Development of automatic surveillance of animal behaviour and welfare using image analysis and machine learned segmentation technique M Nilsson, AH Herlin, H Ardö, O Guzhva, K Åström, C Bergsten Animal 9 (11), 1859-1865, 2015	81	2015
Fast optimal three view triangulation M Byröd, K Josephson, K Åström Computer Vision–ACCV 2007: 8th Asian Conference on Computer Vision, Tokyo …, 2007	81	2007

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