This paper deals with robotic lever control using Explainable Deep Reinforcement Learning. First, we train a policy by using the Deep Deterministic Policy Gradient algorithm and the Hindsight Experience Replay technique, ...

This paper presents a novel procedure for robotic scanning of weld grooves in large tubular T-joints. The procedure is designed to record the discrete weld groove scans using a commercially available line laser scanner ...

Bakgrunn Det stilles store krav til digitalisering av helse- og omsorgssektoren i Norge. Det er behov for en bærekraftig helse- og omsorgssektor som utnytter mulighetene teknologien kan tilføre for effektiv løsning av ulike ...

Being able to robustly reconstruct 3D faces from 2D images is a topic of pivotal importance for a variety of computer vision branches, such as face analysis and face recognition, whose applications are steadily growing. ...

A new stable return-mapping algorithm enables crystal-plasticity solutions by using a regularized yield surface with very large exponents, for which the rate-independent limit of the Schmid assumption in practice is reached. ...

Accurate day-ahead nominations of grid losses in electrical distribution networks are important to reduce the societal cost of these losses. We present a modification of the CatBoost ensemble-based system for day-ahead ...

We propose a novel methodology for the detection and analysis of visual anomalies on challenging surfaces (metallic). The method is based on a local assessment of the reflectance across the inspected surface, using Reflectance ...

Finding and fitting circles from a set of points is a frequent problem in the data analysis of high-energy physics experiments. In a tracker immersed in a homogeneous magnetic field, tracks are close to perfect circles if ...

Deep convolutional neural networks have proven effective in computer vision, especially in the task of image classification. Nevertheless, the success is limited to supervised learning approaches, requiring extensive amounts ...