Kalle Åström

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Anders HeydenProfessor in Mathematics, Lund University確認したメールアドレス: maths.lth.se
Magnus OskarssonAss. professor of mathematics, Lund University確認したメールアドレス: maths.lth.se
Fredrik KahlProfessor, Chalmers University of Technology確認したメールアドレス: chalmers.se
Martin ByrödLunds universitet確認したメールアドレス: maths.lth.se
Hakan ArdoLund University確認したメールアドレス: maths.lth.se
Niels Chr OvergaardLunds Universitet確認したメールアドレス: math.lth.se
Ida ArvidssonPostdoctoral Researcher, Centre for Mathematical Sciences, Lund University確認したメールアドレス: math.lth.se
Viktor LarssonAssistant Professor at Lund University確認したメールアドレス: math.lth.se
Mikael NilssonLund University確認したメールアドレス: math.lth.se
Olof EnqvistAssistant Professor, Department of Signals and Systems, Chalmers University of Technology, Göteborg確認したメールアドレス: chalmers.se
Anders Ericsson確認したメールアドレス: acreo.se
Fredrik TufvessonProfessor, Lund University, Sweden確認したメールアドレス: eit.lth.se
Oleksiy GuzhvaDepartment of Biosystems and Technology, Swedish University of Agricultural Sciences確認したメールアドレス: slu.se
Gabrielle FloodPostdoctoral Researcher, Centre for Mathematical Sciences, Lund University確認したメールアドレス: math.lth.se
Anders BjartellProfessor i Urologi確認したメールアドレス: med.lu.se
Zhayida SimayijiangLund university確認したメールアドレス: maths.lth.se
Martin LarssonPhD, Centre for Mathematical Sciences, Lund University確認したメールアドレス: math.lth.se
Kenneth BatstoneLund University確認したメールアドレス: math.lth.se
Tomas PajdlaAssociate professor, Czech Technical University in Prague確認したメールアドレス: cvut.cz
Fangyuan JiangLund University確認したメールアドレス: maths.lth.se

フォロー

Kalle Åström

Professor, Centre for Mathematical Sciences, Lund University, Sweden

確認したメールアドレス: maths.lth.se - ホームページ

computer vision machine learning structure from sound


タイトル引用回数順公開年順タイトル順	引用先引用先	年
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	436	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	354	1997
Euclidean reconstruction from constant intrinsic parameters K Åström, A Heyden Int. Conf. Pattern Recognition 1, 339-343, 1996	295*	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	219	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	201	2020
Solutions to minimal generalized relative pose problems MO HenrikStewénius, K Aström, D Nistér Citeseer, 2005	177	2005
Robust factorization H Aanæs, R Fisker, K Astrom, JM Carstensen IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (9), 1215-1225, 2002	153	2002
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	149	2017
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
Conjugate gradient bundle adjustment M Byröd, K Åström Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010	127	2010
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	109	2000
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	101	2009
Minimal conditions on intrinsic parameters for euclidean reconstruction A Heyden, K Åström Computer Vision—ACCV'98, 169-176, 1997	101	1997
Generalised epipolar constraints K Åström, R Cipolla, PJ Giblin Computer Vision—ECCV'96: 4th European Conference on Computer Vision …, 1996	92	1996
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	90	2016
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	89	2013
Flexible calibration: Minimal cases for auto-calibration A Heyden, K Astrom Proceedings of the Seventh IEEE International Conference on Computer Vision …, 1999	89	1999
Algebraic properties of multilinear constraints A Heyden, K Åström Mathematical Methods in the Applied Sciences 20 (13), 1135-1162, 1997	89	1997
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	83	2015
Fast optimal three view triangulation M Byröd, K Josephson, K Åström Computer Vision–ACCV 2007: 8th Asian Conference on Computer Vision, Tokyo …, 2007	79	2007

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