12 citations · 21 across the 10 of their papers we have counts for
3 papers · 1 filter
Q-SENN: Quantized Self-Explaining Neural Networks
Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn
Explanations in Computer Vision are often desired, but most Deep Neural Networks can only provide saliency maps with questionable faithfulness. Self-Explaining Neural Networks (SEN…
The voraus-AD Dataset for Anomaly Detection in Robot Applications
Jan Thieß Brockmann, Marco Rudolph, Bodo Rosenhahn +1
During the operation of industrial robots, unusual events may endanger the safety of humans and the quality of production. When collecting data to detect such cases, it is not ensu…
Take 5: Interpretable Image Classification with a Handful of Features
Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn
Deep Neural Networks use thousands of mostly incomprehensible features to identify a single class, a decision no human can follow. We propose an interpretable sparse and low dimens…