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06/09/2022
What should AI see? Using the Public's Opinion to Determine the Perception of an AI
Deep neural networks (DNN) have made impressive progress in the interpre...
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04/29/2022
Tailored Uncertainty Estimation for Deep Learning Systems
Uncertainty estimation bears the potential to make deep learning (DL) sy...
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06/10/2021
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
Many machine learning applications can benefit from simulated data for s...
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01/11/2021
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
Enabling autonomous driving (AD) can be considered one of the biggest ch...
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01/08/2021
Approaching Neural Network Uncertainty Realism
Statistical models are inherently uncertain. Quantifying or at least upp...
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12/14/2020
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates
Instance segmentation with neural networks is an essential task in envir...
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12/02/2020
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation
Despite recent advancements, deep neural networks are not robust against...
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12/02/2020
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs
Deep neural networks are often not robust to semantically-irrelevant cha...
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11/09/2020
Risk Assessment for Machine Learning Models
In this paper we propose a framework for assessing the risk associated w...
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06/15/2020
Self-Supervised Domain Mismatch Estimation for Autonomous Perception
Autonomous driving requires self awareness of its perception functions. ...
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02/20/2020
Strategy to Increase the Safety of a DNN-based Perception for HAD Systems
Safety is one of the most important development goals for highly automat...
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12/16/2019
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation
In semantic segmentation datasets, classes of high importance are oftent...
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12/08/2019
Detection of False Positive and False Negative Samples in Semantic Segmentation
In recent years, deep learning methods have outperformed other methods i...
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07/02/2019
The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation
Neural networks for semantic segmentation can be seen as statistical mod...
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06/17/2019
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks
Most state-of-the-art machine learning (ML) classification systems are v...
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02/12/2019
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
The high amount of sensors required for autonomous driving poses enormou...
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01/24/2019
Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation
As part of autonomous car driving systems, semantic segmentation is an e...
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11/01/2018
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities
We present a method that "meta" classifies whether segments (objects) pr...
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09/27/2018
Introducing Noise in Decentralized Training of Neural Networks
It has been shown that injecting noise into the neural network weights d...
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07/09/2018