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ERRATUM article

Front. Comput. Neurosci., 01 September 2023
Volume 17 - 2023 | https://doi.org/10.3389/fncom.2023.1282093
This article is part of the Research Topic Symmetry as a Guiding Principle in Artificial and Brain Neural Networks, Volume II View all 7 articles

Erratum: Covariance properties under natural image transformations for the generalised Gaussian derivative model for visual receptive fields

This article is an erratum on:

  1. Covariance properties under natural image transformations for the generalised Gaussian derivative model for visual receptive fields

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An Erratum on
Covariance properties under natural image transformations for the generalised Gaussian derivative model for visual receptive fields

by Lindeberg, T. (2023). Front. Comput. Neurosci. 17:1189949. doi: 10.3389/fncom.2023.1189949

Due to a production error, there was a mistake in Footnote 2 in the HTML version of the article. A correction has been made to the mathematical expression. The corrected footnote appears below.

2. In the deep learning literature, the property that we refer to as “covariance” is often referred to as “equivariance.” In this paper, we use the term “covariance” because of the traditional use of this terminology in physics, and to maintain consistency with the previous work in scale-space theory that this paper builds upon. An operator O is said to be covariant under a transformation group Tp with parameter p, if the operator essentially commutes with the transformation group, in the sense that O'(Tp(f)) = Tp(Of) for some possibly transformed operator O' within the same family of operators as O.

The publisher apologizes for this mistake. The original article has been updated.

Keywords: receptive field, Image transformations, scale covariance, affine covariance, Galilean covariance, primary visual cortex, vision, theoretical neuroscience

Citation: Frontiers Production Office (2023) Erratum: Covariance properties under natural image transformations for the generalised Gaussian derivative model for visual receptive fields. Front. Comput. Neurosci. 17:1282093. doi: 10.3389/fncom.2023.1282093

Received: 23 August 2023; Accepted: 23 August 2023;
Published: 01 September 2023.

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Frontiers Editorial Office, Frontiers Media SA, Switzerland

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