58 citations · 62 across the 6 of their papers we have counts for
10 papers
Resource-efficient Deep Neural Networks for Automotive Radar Interference Mitigation
Johanna Rock, Wolfgang Roth, Mate Toth +2
Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous vehicles. With a rising number of radar sensors and the so far unregulated a…
End-to-end Keyword Spotting using Neural Architecture Search and Quantization
David Peter, Wolfgang Roth, Franz Pernkopf
This paper introduces neural architecture search (NAS) for the automatic discovery of end-to-end keyword spotting (KWS) models in limited resource environments. We employ a differe…
Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and Quantization
David Peter, Wolfgang Roth, Franz Pernkopf
This paper introduces neural architecture search (NAS) for the automatic discovery of small models for keyword spotting (KWS) in limited resource environments. We employ a differen…
Quantized Neural Networks for Radar Interference Mitigation
Johanna Rock, Wolfgang Roth, Paul Meissner +1
Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous vehicles. Key performance factors are weather resistance and the possibility…
On Resource-Efficient Bayesian Network Classifiers and Deep Neural Networks
Wolfgang Roth, Günther Schindler, Holger Fröning +1
We present two methods to reduce the complexity of Bayesian network (BN) classifiers. First, we introduce quantization-aware training using the straight-through gradient estimator…
Differentiable TAN Structure Learning for Bayesian Network Classifiers
Wolfgang Roth, Franz Pernkopf
Learning the structure of Bayesian networks is a difficult combinatorial optimization problem. In this paper, we consider learning of tree-augmented naive Bayes (TAN) structures fo…