1,502 research outputs found
Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D
We propose an efficient approach for the grouping of local orientations
(points on vessels) via nilpotent approximations of sub-Riemannian distances in
the 2D and 3D roto-translation groups and . In our distance
approximations we consider homogeneous norms on nilpotent groups that locally
approximate , and which are obtained via the exponential and logarithmic
map on . In a qualitative validation we show that the norms provide
accurate approximations of the true sub-Riemannian distances, and we discuss
their relations to the fundamental solution of the sub-Laplacian on .
The quantitative experiments further confirm the accuracy of the
approximations. Quantitative results are obtained by evaluating perceptual
grouping performance of retinal blood vessels in 2D images and curves in
challenging 3D synthetic volumes. The results show that 1) sub-Riemannian
geometry is essential in achieving top performance and 2) that grouping via the
fast analytic approximations performs almost equally, or better, than
data-adaptive fast marching approaches on and .Comment: 18 pages, 9 figures, 3 tables, in review at JMI
Validating a method for the estimate of gait spatio-temporal parameters with IMUs data on healthy and impaired people from two clinical centers
Instrumented gait analysis offers objective clinical outcome assessment. To this purpose, inertial measurement units (IMUs) represent nowadays a very effective solution due to their limited cost, ease of use and improved wearability. The aim of this study was to apply a well-documented IMU-based method to measure gait spatio-temporal parameters in a large number of healthy and gait-impaired subjects, and evaluate its robustness and validity across two clinical centers. Overall, the results of this work represent a robust and reliable foundation for the clinical use of the proposed IMU based method for gait parameters estimation
Levensbeschouwing en maatschappelijke participatie: Is levensbeschouwing nog steeds een motiverende factor?
E-government op een kruispunt van wegen
De afgelopen jaren heeft de elektronische overheid (ook wel e-government genoemd) een steeds duidelijker gezicht gekregen. Een breed palet
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups
We introduce ChebLieNet, a group-equivariant method on (anisotropic)
manifolds. Surfing on the success of graph- and group-based neural networks, we
take advantage of the recent developments in the geometric deep learning field
to derive a new approach to exploit any anisotropies in data. Via discrete
approximations of Lie groups, we develop a graph neural network made of
anisotropic convolutional layers (Chebyshev convolutions), spatial pooling and
unpooling layers, and global pooling layers. Group equivariance is achieved via
equivariant and invariant operators on graphs with anisotropic left-invariant
Riemannian distance-based affinities encoded on the edges. Thanks to its simple
form, the Riemannian metric can model any anisotropies, both in the spatial and
orientation domains. This control on anisotropies of the Riemannian metrics
allows to balance equivariance (anisotropic metric) against invariance
(isotropic metric) of the graph convolution layers. Hence we open the doors to
a better understanding of anisotropic properties. Furthermore, we empirically
prove the existence of (data-dependent) sweet spots for anisotropic parameters
on CIFAR10. This crucial result is evidence of the benefice we could get by
exploiting anisotropic properties in data. We also evaluate the scalability of
this approach on STL10 (image data) and ClimateNet (spherical data), showing
its remarkable adaptability to diverse tasks.Comment: submitted to NeurIPS'21, https://openreview.net/forum?id=WsfXFxqZXR
Determining factors of the effectiveness of IP-based spin-offs:Comparing the Netherlands and the US
Information and Communication Technology and Public Innovation: Assessing the ICT-driven Modernization of Public Administration
The modernization of public administration is a recurring theme on the political and public agenda in many countries. Modernization presupposes innovation. However, is an innovative public administration a contradiction in terminis? If we look at the practice of public administration, and evaluate -from an evolutionary perspective – how public administration has transformed itself during the last 40 years, we actually see a variety of radical and incremental changes. Hence, innovation does take place. This book clearly demonstrates how public administration organizations try to adapt to changing circumstances in their environment in order to secure their legitimacy.
At the same time we see that public administration tries to respond and anticipate to new technological developments as well as to make use of them. In many countries e-government has become the symbol of the way in which ICT has penetrated in the nerves of ministries, local and regional government and all kinds of agencies. In this publication, a number of case studies have been presented in which different kind of ICT-driven innovations have been described and analyzed
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