Peter Schlicht

According to our database1, Peter Schlicht authored at least 36 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2023
What should AI see? Using the public's opinion to determine the perception of an AI.
AI Ethics, November, 2023

2022
Tailored Uncertainty Estimation for Deep Learning Systems.
CoRR, 2022

Traffic Sign Classifiers Under Physical World Realistic Sticker Occlusions: A Cross Analysis Study.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing.
IEEE Signal Process. Mag., 2021

Approaching Neural Network Uncertainty Realism.
CoRR, 2021

Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis.
Proceedings of the IEEE Intelligent Vehicles Symposium Workshops, 2021

Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.
Proceedings of the International Joint Conference on Neural Networks, 2021

From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation.
Proceedings of the International Joint Conference on Neural Networks, 2021

An Unsupervised Temporal Consistency (TC) Loss To Improve the Performance of Semantic Segmentation Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.
CoRR, 2020

Risk Assessment for Machine Learning Models.
CoRR, 2020

Strategy to Increase the Safety of a DNN-based Perception for HAD Systems.
CoRR, 2020

Quality Assurance for Machine Learning - an approach to function and system safeguarding.
Proceedings of the 20th IEEE International Conference on Software Quality, 2020

Focussing Learned Image Compression to Semantic Classes for V2X Applications.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Scalar and Vector Quantization for Learned Image Compression: A Study on the Effects of MSE and GAN Loss in Various Spaces.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Controlled False Negative Reduction of Minority Classes in Semantic Segmentation.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Detection of False Positive and False Negative Samples in Semantic Segmentation.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Making the Relationship between Uncertainty Estimation and Safety Less Uncertain.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Unsupervised Temporal Consistency Metric for Video Segmentation in Highly-Automated Driving.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Using Mixture of Expert Models to Gain Insights into Semantic Segmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Self-Supervised Domain Mismatch Estimation for Autonomous Perception.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Robust Semantic Segmentation by Redundant Networks With a Layer-Specific Loss Contribution and Majority Vote.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs.
Proceedings of the CSCS '20: Computer Science in Cars Symposium, 2020

2019
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation.
CoRR, 2019

GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation.
CoRR, 2019

Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation.
CoRR, 2019

On Low-Bitrate Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation.
Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Unsupervised Domain Adaptation to Improve Image Segmentation Quality Both in the Source and Target Domain.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

On the Robustness of Redundant Teacher-Student Frameworks for Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.
CoRR, 2018

Efficient Decentralized Deep Learning by Dynamic Model Averaging.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Introducing Noise in Decentralized Training of Neural Networks.
Proceedings of the ECML PKDD 2018 Workshops, 2018


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