19 citations · 19 across the 4 of their papers we have counts for
5 papers
Pedestrian Behavior Prediction for Automated Driving: Requirements, Metrics, and Relevant Features
Michael Herman, Jörg Wagner, Vishnu Prabhakaran +6
Automated vehicles require a comprehensive understanding of traffic situations to ensure safe and anticipatory driving. In this context, the prediction of pedestrians is particular…
Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks
Jörg Wagner, Jan Mathias Köhler, Tobias Gindele +3
To verify and validate networks, it is essential to gain insight into their decisions, limitations as well as possible shortcomings of training data. In this work, we propose a pos…
Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation
Jörg Wagner, Volker Fischer, Michael Herman +1
The performance of autonomous systems heavily relies on their ability to generate a robust representation of the environment. Deep neural networks have greatly improved vision-base…
Hierarchical Recurrent Filtering for Fully Convolutional DenseNets
Jörg Wagner, Volker Fischer, Michael Herman +1
Generating a robust representation of the environment is a crucial ability of learning agents. Deep learning based methods have greatly improved perception systems but still fail i…
Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics
Michael Herman, Tobias Gindele, Jörg Wagner +2
Inverse Reinforcement Learning (IRL) describes the problem of learning an unknown reward function of a Markov Decision Process (MDP) from observed behavior of an agent. Since the a…