The human face has evolved to become the most important source of non-verbal information that conveys our affective, cognitive and mental state to others. Apart from human to human communication facial expressions have also become an indispensable componen ...
Curvilinear networks are prevalent in nature and span many different scales, ranging from micron-scale neural structures in the brain to petameter-scale dark-matter arbors binding massive galaxy clusters. Reliably reconstructing them in an automated fashio ...
In this study an algorithm designed for the diagonal stride in classical cross-country skiing was adapted to compute spatio-temporal parameters for uphill ski mountaineering using a ski fixed inertial sensor. Cycle duration, thrust duration, cycle speed, c ...
Imaging modalities such as Electron Microscopy (EM) and Light Microscopy (LM) can now deliver high-quality, high-resolution image stacks of neural structures. Though these imaging modalities can be used to analyze a variety of components that are critical ...
Automatically extracting linear structures from images is a fundamental low-level vision problem with numerous applications in different domains. Centerline detection and radial estimation are the first crucial steps in most Computer Vision pipelines aimin ...
The present study proposes a method based on ski fixed inertial sensors to automatically compute spatio-temporal parameters (phase durations, cycle speed and cycle length) for the diagonal stride in classical cross-country skiing. The proposed system was v ...
The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid deve ...
