Tony Lindeberg

Tony Lindeberg

Kungliga Tekniska högskolan

H-index: 53

Europe-Sweden

About Tony Lindeberg

Tony Lindeberg, With an exceptional h-index of 53 and a recent h-index of 24 (since 2020), a distinguished researcher at Kungliga Tekniska högskolan, specializes in the field of Computer Vision, Scale Space, Recognition, Image Analysis, Neuroscience.

His recent articles reflect a diverse array of research interests and contributions to the field:

Orientation selectivity properties for the affine Gaussian derivative and the affine Gabor models for visual receptive fields

Covariant spatio-temporal receptive fields for neuromorphic computing

Do the receptive fields in the primary visual cortex span a variability over the degree of elongation of the receptive fields?

Covariance properties under natural image transformations for the generalized Gaussian derivative model for visual receptive fields

A time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time

Discrete approximations of Gaussian smoothing and Gaussian derivatives

Joint covariance property under geometric image transformations for spatio-temporal receptive fields according to the generalized Gaussian derivative model for visual receptive …

A time-causal and time-recursive analogue of the Gabor transform

Tony Lindeberg Information

University

Position

Professor of Computer Science - Computational Vision

Citations(all)

26576

Citations(since 2020)

4444

Cited By

23802

hIndex(all)

53

hIndex(since 2020)

24

i10Index(all)

92

i10Index(since 2020)

48

Email

University Profile Page

Kungliga Tekniska högskolan

Google Scholar

View Google Scholar Profile

Tony Lindeberg Skills & Research Interests

Computer Vision

Scale Space

Recognition

Image Analysis

Neuroscience

Top articles of Tony Lindeberg

Title

Journal

Author(s)

Publication Date

Orientation selectivity properties for the affine Gaussian derivative and the affine Gabor models for visual receptive fields

arXiv preprint arXiv:2304.11920

Tony Lindeberg

2024

Covariant spatio-temporal receptive fields for neuromorphic computing

arXiv preprint arXiv:2405.00318

Jens Egholm Pedersen

Jörg Conradt

Tony Lindeberg

2024/5/1

Do the receptive fields in the primary visual cortex span a variability over the degree of elongation of the receptive fields?

arXiv preprint arXiv:2404.04858

Tony Lindeberg

2024/4/7

Covariance properties under natural image transformations for the generalized Gaussian derivative model for visual receptive fields

Frontiers in Computational Neuroscience

Tony Lindeberg

2023/3/17

A time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time

Biological Cybernetics

Tony Lindeberg

2023/1/23

Discrete approximations of Gaussian smoothing and Gaussian derivatives

arXiv preprint arXiv:2311.11317

Tony Lindeberg

2023/11/19

Joint covariance property under geometric image transformations for spatio-temporal receptive fields according to the generalized Gaussian derivative model for visual receptive …

arXiv preprint arXiv:2311.10543

Tony Lindeberg

2023/11/17

A time-causal and time-recursive analogue of the Gabor transform

arXiv preprint arXiv:2308.14512

Tony Lindeberg

2023/8/28

Orientation selectivity of affine Gaussian derivative based receptive fields

arXiv preprint arXiv:2304.11920v2

Tony Lindeberg

2023/4/24

In Memoriam: Jan-Olof Eklundh

IEEE Transactions on Pattern Analysis & Machine Intelligence

Atsuto Maki

Danica Kragic

Hedvig Kjellstrom

Hossein Azizpour

Josephine Sullivan

...

2022/9/1

Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales

Journal of Mathematical Imaging and Vision

Ylva Jansson

Tony Lindeberg

2022/4/11

Scale-covariant and scale-invariant Gaussian derivative networks

Journal of Mathematical Imaging and Vision

Tony Lindeberg

2022/3/22

Normative theory of visual receptive fields

Heliyon

Tony Lindeberg

2021/1/21

Understanding when spatial transformer networks do not support invariance, and what to do about it

Lukas Finnveden

Ylva Jansson

Tony Lindeberg

2021/1/11

Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges

Ylva Jansson

Tony Lindeberg

2021/1/11

The problems with using STNs to align CNN feature maps

Lukas Finnveden

Ylva Jansson

Tony Lindeberg

2020/1/14

MNIST Large Scale data set

Zenodo

Ylva Jansson

Tony Lindeberg

2020

Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade

Journal of Mathematical Imaging and Vision

Tony Lindeberg

2020

Spatial transformations in convolutional networks and invariant recognition

Ylva Jansson

Maksim Maydanskiy

Lukas Finnveden

Tony Lindeberg

2020

Inability of spatial transformations of CNN feature maps to support invariant recognition

arXiv preprint arXiv:2004.14716

Ylva Jansson

Maksim Maydanskiy

Lukas Finnveden

Tony Lindeberg

2020/4/30

See List of Professors in Tony Lindeberg University(Kungliga Tekniska högskolan)