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2020 – today
- 2024
[i23]Liangyu Zhong, Joachim Sicking, Fabian Hüger, Hanno Gottschalk:
VL4AD: Vision-Language Models Improve Pixel-wise Anomaly Detection. CoRR abs/2409.17330 (2024)- 2023
- [j2]Robin Chan
, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk:
What should AI see? Using the public's opinion to determine the perception of an AI. AI Ethics 3(4): 1381-1405 (2023) - [c30]Fabian Hüger, Alexander Poth, Andreas Wittmann, Roland Walgenbach:
An Approach to the Instantiation of the EU AI Act: A Level of Done Derivation and a Case Study from the Automotive Domain. EuroSPI (1) 2023: 111-123 - 2022
- [c29]Yasin Bayzidi, Alen Smajic, Jan David Schneider, Fabian Hüger, Ruby Moritz, Alois C. Knoll:
Performance Limiting Factors of Deep Neural Networks for Pedestrian Detection. BMVC 2022: 883 - [c28]Andreas Bär, Marvin Klingner, Jonas Löhdefink, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder. CVPR Workshops 2022: 4398-4407 - [c27]Yasin Bayzidi, Alen Smajic, Fabian Hüger, Ruby Moritz, Serin Varghese, Peter Schlicht, Alois C. Knoll:
Traffic Sign Classifiers Under Physical World Realistic Sticker Occlusions: A Cross Analysis Study. IV 2022: 644-650 - [i22]Joachim Sicking, Maram Akila, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Tailored Uncertainty Estimation for Deep Learning Systems. CoRR abs/2204.13963 (2022) - [i21]Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk:
What should AI see? Using the Public's Opinion to Determine the Perception of an AI. CoRR abs/2206.04776 (2022) - 2021
- [j1]Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing. IEEE Signal Process. Mag. 38(1): 42-52 (2021) - [c26]Serin Varghese, Sharat Gujamagadi, Marvin Klingner, Nikhil Kapoor, Andreas Bär, Jan David Schneider, Kira Maag, Peter Schlicht, Fabian Hüger, Tim Fingscheidt:
An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks. CVPR Workshops 2021: 12-20 - [c25]Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz:
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation. CVPR Workshops 2021: 85-92 - [c24]Nikhil Kapoor, Andreas Bär, Serin Varghese, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation. IJCNN 2021: 1-8 - [c23]Kira Maag, Matthias Rottmann, Serin Varghese, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. IJCNN 2021: 1-8 - [c22]Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz:
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. IV Workshops 2021: 182-189 - [c21]Michael Mock, Stephan Scholz, Frédérik Blank, Fabian Hüger, Andreas J. Rohatschek, Loren Schwarz, Thomas Stauner:
An Integrated Approach to a Safety Argumentation for AI-Based Perception Functions in Automated Driving. SAFECOMP Workshops 2021: 265-271 - [i20]Joachim Sicking, Alexander Kister, Matthias Fahrland, Stefan Eickeler, Fabian Hüger, Stefan Rüping, Peter Schlicht, Tim Wirtz:
Approaching Neural Network Uncertainty Realism. CoRR abs/2101.02974 (2021) - [i19]Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin J. Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing. CoRR abs/2101.03924 (2021) - [i18]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Nico Piatkowski, Christian Bauckhage:
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving. CoRR abs/2104.07538 (2021) - [i17]Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz:
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation. CoRR abs/2104.09254 (2021) - [i16]Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz:
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. CoRR abs/2106.05549 (2021) - 2020
- [c20]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CSCS 2020: 3:1-3:8 - [c19]Andreas Bär, Marvin Klingner, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
Robust Semantic Segmentation by Redundant Networks With a Layer-Specific Loss Contribution and Majority Vote. CVPR Workshops 2020: 1348-1358 - [c18]Jonas Löhdefink, Justin Fehrling, Marvin Klingner, Fabian Hüger, Peter Schlicht, Nico M. Schmidt, Tim Fingscheidt:
Self-Supervised Domain Mismatch Estimation for Autonomous Perception. CVPR Workshops 2020: 1359-1368 - [c17]Serin Varghese, Yasin Bayzidi, Andreas Bär, Nikhil Kapoor, Sounak Lahiri, Jan David Schneider, Nico M. Schmidt, Peter Schlicht, Fabian Hüger, Tim Fingscheidt:
Unsupervised Temporal Consistency Metric for Video Segmentation in Highly-Automated Driving. CVPR Workshops 2020: 1369-1378 - [c16]Svetlana Pavlitskaya, Christian Hubschneider, Michael Weber, Ruby Moritz, Fabian Hüger, Peter Schlicht, J. Marius Zöllner:
Using Mixture of Expert Models to Gain Insights into Semantic Segmentation. CVPR Workshops 2020: 1399-1406 - [c15]Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Detection of False Positive and False Negative Samples in Semantic Segmentation. DATE 2020: 1351-1356 - [c14]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Nico Piatkowski, Christian Bauckhage:
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving. ICPR 2020: 10203-10210 - [c13]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. IJCNN 2020: 1-8 - [c12]Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. IJCNN 2020: 1-9 - [c11]Jonas Löhdefink, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
Scalar and Vector Quantization for Learned Image Compression: A Study on the Effects of MSE and GAN Loss in Various Spaces. ITSC 2020: 1-8 - [c10]Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
Focussing Learned Image Compression to Semantic Classes for V2X Applications. IV 2020: 1641-1648 - [i15]Timo Sämann, Peter Schlicht, Fabian Hüger:
Strategy to Increase the Safety of a DNN-based Perception for HAD Systems. CoRR abs/2002.08935 (2020) - [i14]Jonas Löhdefink, Justin Fehrling, Marvin Klingner, Fabian Hüger, Peter Schlicht, Nico M. Schmidt, Tim Fingscheidt:
Self-Supervised Domain Mismatch Estimation for Autonomous Perception. CoRR abs/2006.08613 (2020) - [i13]Paul Schwerdtner, Florens Greßner, Nikhil Kapoor, Felix Assion, René Sass, Wiebke Günther, Fabian Hüger, Peter Schlicht:
Risk Assessment for Machine Learning Models. CoRR abs/2011.04328 (2020) - [i12]Laura von Rüden, Tim Wirtz, Fabian Hüger, Jan David Schneider, Christian Bauckhage:
Towards Map-Based Validation of Semantic Segmentation Masks. CoRR abs/2011.08008 (2020) - [i11]Nikhil Kapoor, Chun Yuan, Jonas Löhdefink, Roland Zimmermann, Serin Varghese, Fabian Hüger, Nico M. Schmidt, Peter Schlicht, Tim Fingscheidt:
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs. CoRR abs/2012.01386 (2020) - [i10]Nikhil Kapoor, Andreas Bär, Serin Varghese, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation. CoRR abs/2012.01558 (2020) - [i9]Kira Maag, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. CoRR abs/2012.07504 (2020)
2010 – 2019
- 2019
- [c9]Felix Assion, Peter Schlicht, Florens Greßner, Wiebke Günther, Fabian Hüger, Nico M. Schmidt, Umair Rasheed:
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks. CVPR Workshops 2019: 1370-1379 - [c8]Andreas Bär, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
On the Robustness of Redundant Teacher-Student Frameworks for Semantic Segmentation. CVPR Workshops 2019: 1380-1388 - [c7]Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. CVPR Workshops 2019: 1395-1403 - [c6]Jan-Aike Bolte, Markus Kamp, Antonia Breuer, Silviu Homoceanu, Peter Schlicht, Fabian Hüger, Daniel Lipinski, Tim Fingscheidt:
Unsupervised Domain Adaptation to Improve Image Segmentation Quality Both in the Source and Target Domain. CVPR Workshops 2019: 1404-1413 - [c5]Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
On Low-Bitrate Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation. IV 2019: 424-431 - [i8]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation. CoRR abs/1901.08394 (2019) - [i7]Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt:
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation. CoRR abs/1902.04311 (2019) - [i6]Felix Assion, Peter Schlicht, Florens Greßner, Wiebke Günther, Fabian Hüger, Nico M. Schmidt, Umair Rasheed:
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks. CoRR abs/1906.07077 (2019) - [i5]Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation. CoRR abs/1907.01342 (2019) - [i4]Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Detection of False Positive and False Negative Samples in Semantic Segmentation. CoRR abs/1912.03673 (2019) - [i3]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation. CoRR abs/1912.07420 (2019) - 2018
- [c4]Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Efficient Decentralized Deep Learning by Dynamic Model Averaging. ECML/PKDD (1) 2018: 393-409 - [i2]Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Efficient Decentralized Deep Learning by Dynamic Model Averaging. CoRR abs/1807.03210 (2018) - [i1]Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. CoRR abs/1811.00648 (2018) - 2014
- [b1]Fabian Hüger:
Eine flexible Bedien- und Anzeigeschnittstelle für Erweiterungen in Fahrerinformationssystemen. University of Kassel, Logos-Verlag 2014, ISBN 978-3-8325-3862-0, pp. 1-103 - 2012
- [c3]Fabian Hüger:
Eine abgesicherte Bedien-und Anzeigeschnittstelle zur Integration von Smartphone-Anwendungen in die Benutzeroberfläche von Fahrerinformationssystemen. GI-Jahrestagung 2012: 817-822 - [c2]Fabian Hüger:
Platform independent applications for in-vehicle infotainment systems via integration of CE devices. ICCE-Berlin 2012: 221-222 - 2011
- [c1]Fabian Hüger:
User interface transfer for driver information systems: a survey and an improved approach. AutomotiveUI 2011: 113-120
Coauthor Index
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last updated on 2024-10-18 19:29 CEST by the dblp team
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