41 citations · 58 across the 7 of their papers we have counts for
4 papers · 1 filter
Improving Uncertainty of Deep Learning-based Object Classification on Radar Spectra using Label Smoothing
Kanil Patel, William Beluch, Kilian Rambach +2
Object type classification for automotive radar has greatly improved with recent deep learning (DL) solutions, however these developments have mostly focused on the classification…
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities
Elias Eulig, Piyapat Saranrittichai, Chaithanya Kumar Mummadi +4
Common deep neural networks (DNNs) for image classification have been shown to rely on shortcut opportunities (SO) in the form of predictive and easy-to-represent visual factors. T…
Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation
Chaithanya Kumar Mummadi, Robin Hutmacher, Kilian Rambach +3
Deep neural networks often exhibit poor performance on data that is unlikely under the train-time data distribution, for instance data affected by corruptions. Previous works demon…
Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra
Kanil Patel, William Beluch, Kilian Rambach +3
Deep learning (DL) has recently attracted increasing interest to improve object type classification for automotive radar.In addition to high accuracy, it is crucial for decision ma…