3 citations · 8 across the 5 of their papers we have counts for
3 papers · 1 filter
Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception
Anne Sielemann, Valentin Barner, Stefan Wolf +3
Common approaches to explainable AI (XAI) for deep learning focus on analyzing the importance of input features on the classification task in a given model: saliency methods like S…
Synset Signset Germany: a Synthetic Dataset for German Traffic Sign Recognition
Anne Sielemann, Lena Loercher, Max-Lion Schumacher +3
In this paper, we present a synthesis pipeline and dataset for training / testing data in the task of traffic sign recognition that combines the advantages of data-driven and analy…
Continual Learning for Class- and Domain-Incremental Semantic Segmentation
Tobias Kalb, Masoud Roschani, Miriam Ruf +1
The field of continual deep learning is an emerging field and a lot of progress has been made. However, concurrently most of the approaches are only tested on the task of image cla…