Publications
[Extracted from DiVA,
the publication database at KTH.]
- Jansson, Y.; Lindeberg, T. (2022):
- Scale-invariant scale-channel networks - Deep networks that generalise to previously unseen scales.
- Journal of Mathematical Imaging and Vision 64: 506-536 [Details]
- Lindeberg, T. (2022):
- A time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time.
- Report [Details]
- Lindeberg, T. (2022):
- Scale-covariant and scale-invariant Gaussian derivative networks.
- Journal of Mathematical Imaging and Vision 64: 223-242 [Details]
- Jansson, Y.; Lindeberg, T. (2021):
- Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales.
- Manuscript (preprint) [Details]
- Lindeberg, T. (2021):
- Scale-covariant and scale-invariant Gaussian derivative networks.
- [Conference paper] SSVM 2021: 8th International Conference on Scale Space and Variational Methods in Computer Vision, May 16-20, 2021.; Scale Space and Variational Methods in Computer Vision 3-14 [Details]
- Lindeberg, T. (2021):
- Normative theory of visual receptive fields.
- Heliyon 7: e05897-1-e05897-20 [Details]
- Finnveden, L.; Jansson, Y.; Lindeberg, T. (2021):
- Understanding when spatial transformer networks do not support invariance, and what to do about it.
- [Conference paper] ICPR 2020: 25th International Conference on Pattern Recognition, Milan, Italy, January 10-15, 2021; ICPR 2020: International Conference on Pattern Recognition 3427-3434 [Details]
- Jansson, Y.; Lindeberg, T. (2021):
- Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges.
- [Conference paper] ICPR 2020: 25th International Conference on Pattern Recognition, Milan, Italy, January 10-15, 2021; ICPR 2020: International Conference on Pattern Recognition 1181-1188 [Details]
- Lindeberg, T. (2021):
- Scale selection.
- Chapter in book [Details]
- Jansson, Y.; Maydanskiy, M.; Finnveden, L.; Lindeberg, T. (2020):
- Spatial transformations in convolutional networks and invariant recognition..
- [Conference paper] DeepMath2020 Conference on the Mathematical Theory of Deep Neural Networks Nov 5 - Nov 6, 2020; [Details]
- Lindeberg, T. (2020):
- Scale-covariant and scale-invariant Gaussian derivative networks.
- Report [Details]
- Jansson, Y.; Lindeberg, T. (2020):
- MNIST Large Scale data set.
- Data set [Details]
- Jansson, Y.; Maydanskiy, M.; Finnveden, L.; Lindeberg, T. (2020):
- Inability of spatial transformations of CNN feature maps to support invariant recognition.
- Report [Details]
- Finnveden, L.; Jansson, Y.; Lindeberg, T. (2020):
- Understanding when spatial transformer networks do not support invariance, and what to do about it.
- Manuscript (preprint) [Details]
- Jansson, Y.; Lindeberg, T. (2020):
- Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges.
- Manuscript (preprint) [Details]
- Lindeberg, T. (2020):
- Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade.
- Journal of Mathematical Imaging and Vision 62: 120-148 [Details]
- Finnveden, L.; Jansson, Y.; Lindeberg, T. (2020):
- The problems with using STNs to align CNN feature maps.
- [Conference paper] Northern Lights Deep Learning Workshop 2020, Tromsø, Norway, 20-21 Jan 2020; [Details]
- Lindeberg, T. (2019):
- Provably scale-covariant networks from oriented quasi quadrature measures in cascade.
- [Conference paper] 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019; Hofgeismar; Germany; 30 June 2019 through 4 July 2019; Scale Space and Variational Methods in Computer Vision 328-340 [Details]
- Friberg, A.; Lindeberg, T.; Hellwagner, M.; Helgason, P.; Salomão, G.; Elovsson, A.; Lemaitre, G.; Ternström, S. (2018):
- Prediction of three articulatory categories in vocal sound imitations using models for auditory receptive fields.
- Journal of the Acoustical Society of America 144: 1467-1483 [Details]
- Lindeberg, T. (2018):
- Dense scale selection over space, time and space-time.
- SIAM Journal on Imaging Sciences 11: 407-441 [Details]
- Lindeberg, T. (2018):
- Spatio-temporal scale selection in video data.
- Journal of Mathematical Imaging and Vision 60: 525-562 [Details]
- Jansson, Y.; Lindeberg, T. (2018):
- Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields.
- Journal of Mathematical Imaging and Vision 60: 1369-1398 [Details]
- Jansson, Y.; Lindeberg, T. (2017):
- Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields.
- Report [Details]
- Lindeberg, T. (2017):
- Discrete approximations of the affine Gaussian derivative model for visual receptive fields.
- Report [Details]
- Jansson, Y.; Lindeberg, T. (2017):
- Dynamic texture recognition using time-causal spatio-temporal scale-space filters.
- [Conference paper] SSVM 2017: 6th International Conference on Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, June 4-8, 2017; Scale Space and Variational Methods in Computer Vision 16-28 [Details]
- Lindeberg, T. (2017):
- Spatio-temporal scale selection in video data.
- [Conference paper] SSVM 2017: 6th International Conference on Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, June 4-8, 2017; Scale Space and Variational Methods in Computer Vision 3-15 [Details]
- Lindeberg, T. (2017):
- Temporal scale selection in time-causal scale space.
- Journal of Mathematical Imaging and Vision 58: 57-101 [Details]
- Lindeberg, T. (2017):
- Normative theory of visual receptive fields.
- Report [Details]
- Lindeberg, T. (2017):
- Discrete approximations of affine Gaussian receptive fields.
- Report [Details]
- Lindeberg, T. (2016):
- Time-causal and time-recursive spatio-temporal receptive fields for computer vision and computational modelling of biological vision.
- [Conference paper] International Workshop on Geometry, PDE’s and Lie Groups in Image Analysis, Eindhoven, The Netherlands, August 24-26, 2016.; International Workshop on Geometry, PDE’s and Lie Groups in Image Analysis, Eindhoven, The Netherlands, August 24-26, 2016. [Details]
- Lindeberg, T. (2016):
- Time-causal and time-recursive receptive fields for invariance and covariance under natural image transformations.
- [Conference paper] First European Machine Vision Forum, Heidelberg, Germany, September 8-9, 2016.; [Details]
- Lindeberg, T. (2016):
- Time-causal and time-recursive spatio-temporal receptive fields.
- Journal of Mathematical Imaging and Vision 55: 50-88 [Details]
- Ekeberg, Ö.; Fransén, E.; Hellgren Kotaleski, J.; Herman, P.; Kumar, A.; Lansner, A.; Lindeberg, T. (2016):
- Computational Brain Science at CST, CSC, KTH.
- Other [Details]
- Lindeberg, T.; Friberg, A. (2015):
- Idealized computational models for auditory receptive fields.
- PLOS ONE 10: [Details]
- Lindeberg, T.; Friberg, A. (2015):
- Scale-space theory for auditory signals.
- [Conference paper] SSVM 2015: Fifth International Conference on Scale Space and Variational Methods in Computer Vision, Lège Cap Ferret, France, 31 May - 4 June, 2015; Scale Space and Variational Methods in Computer Vision 3-15 [Details]
- Lindeberg, T. (2015):
- Separable time-causal and time-recursive spatio-temporal receptive fields.
- [Conference paper] SSVM 2015: Fifth International Conference on Scale Space and Variational Methods in Computer Vision, Lège Cap Ferret, France, 31 May - 4 June, 2015; Scale Space and Variational Methods in Computer Vision 90-102 [Details]
- Lindeberg, T. (2015):
- Image matching using generalized scale-space interest points.
- Journal of Mathematical Imaging and Vision 52: 3-36 [Details]
- Lindeberg, T. (2015):
- Time-causal and time-recursive spatio-temporal receptive fields.
- Report [Details]
- Lindeberg, T. (2014):
- Scale selection.
- Chapter in book [Details]
- Lindeberg, T. (2013):
- Invariance of visual operations at the level of receptive fields.
- [Conference paper] CNS 2013: 22nd Annual Computational Neuroscience Meeting, July 13-18, Paris, France. BMC Neuroscience 14(Suppl 1); P242 [Details]
- Lindeberg, T. (2013):
- A framework for invariant visual operations based on receptive field responses.
- [Conference paper] SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, Schloss Seggau, Graz region, Austria; SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, Schloss Seggau, Graz region, Austria [Details]
- Lindeberg, T. (2013):
- Invariance of visual operations at the level of receptive fields.
- PLOS ONE 8: e66990-1-e66990-33 [Details]
- Lindeberg, T. (2013):
- A computational theory of visual receptive fields.
- Biological Cybernetics 107: 589-635 [Details]
- Lindeberg, T. (2013):
- Generalized axiomatic scale-space theory.
- Chapter in book [Details]
- Lindeberg, T. (2013):
- Image matching using generalized scale-space interest points.
- [Conference paper] SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, 2013, Schloss Seggau, Graz region, Austria; Scale Space and Variational Methods in Computer Vision: 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, , June 2-6, 2013, Proceedings 355-367 [Details]
- Lindeberg, T. (2013):
- Scale Selection Properties of Generalized Scale-Space Interest Point Detectors.
- Journal of Mathematical Imaging and Vision 46: 177-210 [Details]
- Lindeberg, T. (2012):
- Scale invariant feature transform.
- Other [Details]
- Linde, O.; Lindeberg, T. (2012):
- Composed Complex-Cue Histograms - An Investigation of the Information Content in Receptive Field Based Image Descriptors for Object Recognition.
- Computer Vision and Image Understanding 116: 538-560 [Details]
- Lindeberg, T. (2011):
- Generalized Gaussian Scale-Space Axiomatics Comprising Linear Scale-Space, Affine Scale-Space and Spatio-Temporal Scale-Space.
- Journal of Mathematical Imaging and Vision 40: 36-81 [Details]
- Lindeberg, T. (2009):
- Scale-Space.
- Chapter in book [Details]
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