Search Results for author: Jörg Wagner

Found 5 papers, 0 papers with code

Pedestrian Behavior Prediction for Automated Driving: Requirements, Metrics, and Relevant Features

no code implementations15 Dec 2020 Michael Herman, Jörg Wagner, Vishnu Prabhakaran, Nicolas Möser, Hanna Ziesche, Waleed Ahmed, Lutz Bürkle, Ernst Kloppenburg, Claudius Gläser

In this paper, we thoroughly analyze the requirements on pedestrian behavior prediction for automated driving via a system-level approach.

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks

no code implementations7 Aug 2019 Jörg Wagner, Jan Mathias Köhler, Tobias Gindele, Leon Hetzel, Jakob Thaddäus Wiedemer, Sven Behnke

Our approach is based on a novel technique to defend against adversarial evidence (i. e. faulty evidence due to artefacts) by filtering gradients during optimization.

Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation

no code implementations9 Oct 2018 Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke

Our filter module splits the filter task into multiple less complex and more interpretable subtasks.

Hierarchical Recurrent Filtering for Fully Convolutional DenseNets

no code implementations5 Oct 2018 Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke

Generating a robust representation of the environment is a crucial ability of learning agents.

Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics

no code implementations13 Apr 2016 Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard

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.

Transfer Learning

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