activity
20242026
most citedRelationships between the degrees of freedom in the affine Gaussian derivative model for visual receptive fields and 2-D affine image transformations, with application to covariance properties of simple cells in the primary visual cortex

3 citations · 6 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2026

Scale-invariant Gaussian derivative residual networks

Andrzej Perzanowski, Tony Lindeberg

Generalisation across image scales remains a fundamental challenge for deep networks, which often fail to handle images at scales not seen during training (the out-of-distribution…

cs.CV2025

Hybrid Lie semi-group and cascade structures for the generalized Gaussian derivative model for visual receptive fields

Tony Lindeberg

Because of the variabilities of real-world image structures under the natural image transformations that arise when observing similar objects or spatio-temporal events under differ…