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mathematische Modellierung
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Uncertainty Quantification for Object Detection: Output- and Gradient-Based Approaches
The Good and the Bad: Using Neuron Coverage as a DNN Validation Technique
Safety Assurance of Machine Learning for Perception Functions
Optimized Data Synthesis for DNN Training and Validation by Sensor Artifact Simulation
Joint Optimization for DNN Model Compression and Corruption Robustness
Invertible Neural Networks for Understanding Semantics of Invariances of CNN Representations
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Improved DNN Robustness by Multi-task Training with an Auxiliary Self-Supervised Task
Evaluating Mixture-of-Experts Architectures for Network Aggregation
Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance?
Detecting and Learning the Unknown in Semantic Segmentation
Confidence Calibration for Object Detection and Segmentation
A Variational Deep Synthesis Approach for Perception Validation
Analysis and Comparison of Datasets by Leveraging Data Distributions in Latent Spaces