53 citations
- Technical University of MunichDE4 papers
- AppPeople (Germany)DE1 paper
- Fraunhofer Institute for Applied and Integrated SecurityDE1 paper
- German Research Centre for Artificial IntelligenceDE1 paper
- LMU KlinikumDE1 paper
- Ludwig-Maximilians-Universität MünchenDE1 paper
- RWTH Aachen UniversityDE1 paper
- Saarland UniversityDE1 paper
- Siemens Healthineers (Germany)DE1 paper
- The Royal Melbourne HospitalAU1 paper
- Universidade Federal do ParanáBR1 paper
- University of Castilla-La ManchaES1 paper
4 papers · 1 filter
High-Dimensional Confidence Regions in Sparse MRI
Frederik Hoppe, Felix Krahmer, Claudio Mayrink Verdun +2
One of the most promising solutions for uncertainty quantification in high-dimensional statistics is the debiased LASSO that relies on unconstrained -minimization. The init…
High Precision Indoor Navigation for Autonomous Vehicles
Eduardo Sánchez Morales, Michael Botsch, Bertold Huber +1
Autonomous driving is an important trend of the automotive industry. The continuous research towards this goal requires a precise reference vehicle state estimation under all circu…
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification
Friedrich Kruber, Jonas Wurst, Eduardo Sánchez Morales +2
The goal of this paper is to provide a method, which is able to find categories of traffic scenarios automatically. The architecture consists of three main components: A microscopi…
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization
Friedrich Kruber, Jonas Wurst, Michael Botsch
A modification of the Random Forest algorithm for the categorization of traffic situations is introduced in this paper. The procedure yields an unsupervised machine learning method…