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mathematische Modellierung
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Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Confidence Calibration for Object Detection and Segmentation
The Good and the Bad: Using Neuron Coverage as a DNN Validation Technique
Evaluating Mixture-of-Experts Architectures for Network Aggregation
Detecting and Learning the Unknown in Semantic Segmentation
Safety Assurance of Machine Learning for Perception Functions
Optimized Data Synthesis for DNN Training and Validation by Sensor Artifact Simulation
Invertible Neural Networks for Understanding Semantics of Invariances of CNN Representations
Joint Optimization for DNN Model Compression and Corruption Robustness