58 citations · 119 across the 14 of their papers we have counts for
27 papers
Variational Message Passing-Based Respiratory Motion Estimation and Detection Using Radar Signals
Jakob Möderl, Erik Leitinger, Franz Pernkopf +1
We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using multistatic ultra-wideband (UWB) radar. In…
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…
Distribution Mismatch Correction for Improved Robustness in Deep Neural Networks
Alexander Fuchs, Christian Knoll, Franz Pernkopf
Deep neural networks rely heavily on normalization methods to improve their performance and learning behavior. Although normalization methods spurred the development of increasingl…
Lung Sound Classification Using Co-tuning and Stochastic Normalization
Truc Nguyen, Franz Pernkopf
In this paper, we use pre-trained ResNet models as backbone architectures for classification of adventitious lung sounds and respiratory diseases. The knowledge of the pre-trained…
Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolitional Neural Networks
Truc Nguyen, Franz Pernkopf
Large annotated lung sound databases are publicly available and might be used to train algorithms for diagnosis systems. However, it might be a challenge to develop a well-performi…
Complex-valued Convolutional Neural Networks for Enhanced Radar Signal Denoising and Interference Mitigation
Alexander Fuchs, Johanna Rock, Mate Toth +2
Autonomous driving highly depends on capable sensors to perceive the environment and to deliver reliable information to the vehicles' control systems. To increase its robustness, a…