41 citations · 141 across the 25 of their papers we have counts for
6 papers · 1 filter
Probabilistic Active Learning for Active Class Selection
Daniel Kottke, Georg Krempl, Marianne Stecklina +6
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask the oracle to provide an instance for that class to optimize a classifier's perf…
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information
Stefan Zernetsch, Oliver Trupp, Viktor Kress +2
This article presents a novel approach to incorporate visual cues from video-data from a wide-angle stereo camera system mounted at an urban intersection into the forecast of cycli…
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories
Viktor Kress, Fabian Jeske, Stefan Zernetsch +2
In this article, an approach for probabilistic trajectory forecasting of vulnerable road users (VRUs) is presented, which considers past movements and the surrounding scene. Past m…
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders
Felix Möller, Diego Botache, Denis Huseljic +3
Deep neural networks often suffer from overconfidence which can be partly remedied by improved out-of-distribution detection. For this purpose, we propose a novel approach that all…
Cyclist Intention Detection: A Probabilistic Approach
Stefan Zernetsch, Hannes Reichert, Viktor Kress +2
This article presents a holistic approach for probabilistic cyclist intention detection. A basic movement detection based on motion history images (MHI) and a residual convolutiona…
CLeaR: An Adaptive Continual Learning Framework for Regression Tasks
Yujiang He, Bernhard Sick
Catastrophic forgetting means that a trained neural network model gradually forgets the previously learned tasks when being retrained on new tasks. Overcoming the forgetting proble…