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Peter Schlicht
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2020 – today
- 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) - 2022
- [c25]Andreas Bär
Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder. CVPR Workshops 2022: 4398-4407 - [c24]Yasin Bayzidi, Alen Smajic
Traffic Sign Classifiers Under Physical World Realistic Sticker Occlusions: A Cross Analysis Study. IV 2022: 644-650 - [i20]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) - [i19]Robin Chan
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
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) - [c23]Serin Varghese, Sharat Gujamagadi, Marvin Klingner, Nikhil Kapoor, Andreas Bär
An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks. CVPR Workshops 2021: 12-20 - [c22]Nikhil Kapoor, Andreas Bär
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation. IJCNN 2021: 1-8 - [c21]Kira Maag
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. IJCNN 2021: 1-8 - [c20]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 - [i18]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) - [i17]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) - [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
- [c19]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 - [c18]Andreas Bär
Robust Semantic Segmentation by Redundant Networks With a Layer-Specific Loss Contribution and Majority Vote. CVPR Workshops 2020: 1348-1358 - [c17]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 - [c16]Serin Varghese
Unsupervised Temporal Consistency Metric for Video Segmentation in Highly-Automated Driving. CVPR Workshops 2020: 1369-1378 - [c15]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 - [c14]Vincent Aravantinos, Peter Schlicht:
Making the Relationship between Uncertainty Estimation and Safety Less Uncertain. DATE 2020: 1139-1144 - [c13]Matthias Rottmann, Kira Maag
Detection of False Positive and False Negative Samples in Semantic Segmentation. DATE 2020: 1351-1356 - [c12]Robin Chan
Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. IJCNN 2020: 1-8 - [c11]Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. IJCNN 2020: 1-9 - [c10]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 - [c9]Jonas Löhdefink, Andreas Bär
Focussing Learned Image Compression to Semantic Classes for V2X Applications. IV 2020: 1641-1648 - [c8]Alexander Poth, Burkhard Meyer, Peter Schlicht, Andreas Riel:
Quality Assurance for Machine Learning - an approach to function and system safeguarding. QRS 2020: 22-29 - [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]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) - [i11]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) - [i10]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
- [c7]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 - [c6]Andreas Bär
On the Robustness of Redundant Teacher-Student Frameworks for Semantic Segmentation. CVPR Workshops 2019: 1380-1388 - [c5]Robin Chan
The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. CVPR Workshops 2019: 1395-1403 - [c4]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 - [c3]Jonas Löhdefink, Andreas Bär
On Low-Bitrate Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation. IV 2019: 424-431 - [i9]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) - [i8]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) - [i7]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) - [i6]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) - [i5]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) - [i4]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
- [c2]Linara Adilova, Nathalie Paul, Peter Schlicht:
Introducing Noise in Decentralized Training of Neural Networks. DMLE/IOTSTREAMING@PKDD/ECML 2018: 37-48 - [c1]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 - [i3]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) - [i2]Linara Adilova, Nathalie Paul, Peter Schlicht:
Introducing Noise in Decentralized Training of Neural Networks. CoRR abs/1809.10678 (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)
Coauthor Index
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