5 papers
Generalized Modulo Hysteresis Encoding
Matthias Beckmann, Jürgen Jeschke
Unlimited sensing and its extension via modulo hysteresis provide an efficient encoding scheme for high dynamic range signals by folding the signal's amplitude into the range of th…
Generalizations of the Normalized Radon Cumulative Distribution Transform for Limited Data Recognition
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT) exploits one-dimensional Wasserstein transport and the Radon transform to represent prominent features in images. It is closely…
Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT), is an easy-to-compute feature extractor that facilitates image classification tasks especially in the small data regime. It is…
Orthogonal Matching Pursuit based Reconstruction for Modulo Hysteresis Operators
Matthias Beckmann, Jürgen Jeschke
Unlimited sampling provides an acquisition scheme for high dynamic range signals by folding the signal into the dynamic range of the analog-to-digital converter (ADC) using modulo…
Max-Normalized Radon Cumulative Distribution Transform for Limited Data Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
The Radon cumulative distribution transform (R-CDT) exploits one-dimensional Wasserstein transport and the Radon transform to represent prominent features in images. It is closely…