3 citations · 7 across the 6 of their papers we have counts for
7 papers · 1 filter
A function space perspective on stochastic shape evolution
Elizabeth Baker, Thomas Besnier, Stefan Sommer
Modelling randomness in shape data, for example, the evolution of shapes of organisms in biology, requires stochastic models of shapes. This paper presents a new stochastic shape m…
An Average of the Human Ear Canal: Recovering Acoustical Properties via Shape Analysis
Sune Darkner, Stefan Sommer, Andreas Schuhmacher +3
Humans are highly dependent on the ability to process audio in order to interact through conversation and navigate from sound. For this, the shape of the ear acts as a mechanical a…
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
Mauricio Orbes Arteaga, Lauge Sørensen, M. Jorge Cardoso +6
For proper generalization performance of convolutional neural networks (CNNs) in medical image segmentation, the learnt features should be invariant under particular non-linear sha…
Latent Space Non-Linear Statistics
Line Kuhnel, Tom Fletcher, Sarang Joshi +1
Given data, deep generative models, such as variational autoencoders (VAE) and generative adversarial networks (GAN), train a lower dimensional latent representation of the data sp…
String Methods for Stochastic Image and Shape Matching
Alexis Arnaudon, Darryl Holm, Stefan Sommer
Matching of images and analysis of shape differences is traditionally pursued by energy minimization of paths of deformations acting to match the shape objects. In the Large Deform…
Stochastic metamorphosis with template uncertainties
Alexis Arnaudon, Darryl Holm, Stefan Sommer
In this paper, we investigate two stochastic perturbations of the metamorphosis equations of image analysis, in the geometrical context of the Euler-Poincaré theory. In the metamor…