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Found 4 papers, 1 papers with code
Online Out-of-Domain Detection for Automated Driving
DNNs learn from training data, which means that they only achieve good accuracy within the underlying data distribution of the training data.
Improving Predictive Performance and Calibration by Weight Fusion in Semantic Segmentation
Albeit effective, only few works haveimproved the understanding and the performance of weight averaging. Here, we revisit this approach and show that a simple weight fusion (WF)strategy can lead to a significantly improved predictive performance andcalibration.
Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments
In order to evaluate our multi-task approach, we extend the annotations of the common RGB-D indoor datasets NYUv2 and SUNRGB-D for instance segmentation and orientation estimation.
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization
Clinical decision support using deep neural networks has become a topic of steadily growing interest.
