Biofilms, present as microorganisms and surviving on surfaces, can increase food cross-
contamination, leading to changes in the food industry's cleaning and disinfection dynamics …

Reliable and efficient trajectory generation methods are a fundamental need for
autonomous dynamical systems. The goal of this article is to provide a comprehensive …

Minimization of regularized losses is a principled approach to weak supervision well-
established in deep learning, in general. However, it is largely overlooked in semantic …

A large number of imaging problems reduce to the optimization of a cost function, with
typical structural properties. The aim of this paper is to describe the state of the art in …

Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

Motion is a strong cue for unsupervised object-level grou**. In this paper, we demonstrate
that motion will be exploited most effectively, if it is regarded over larger time windows …

In this paper, we give a short introduction to machine learning and survey its applications in
radiology. We focused on six categories of applications in radiology: medical image …

Deep learning has been applied to saliency detection in recent years. The superior
performance has proved that deep networks can model the semantic properties of salient …

These notes address various theoretical and practical topics related to Total Variationbased
image reconstruction. They focus first on some theoretical results on functions which …

Implicit representations can provide simple descriptions of relatively complex shapes and
can in many cases be a good choice when designing stable shape processing algorithms …