13 citations · 27 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…
NIFF: Alleviating Forgetting in Generalized Few-Shot Object Detection via Neural Instance Feature Forging
Karim Guirguis, Johannes Meier, George Eskandar +3
Privacy and memory are two recurring themes in a broad conversation about the societal impact of AI. These concerns arise from the need for huge amounts of data to train deep neura…