47 citations · 50 across the 3 of their papers we have counts for
3 papers
eess.SP2020★ 47 cited
Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals
Johanna Rock, Mate Toth, Paul Meissner +1
Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous cars. Key performance factors are a fine range resolution and the possibilit…
eess.SP2020★ 3 cited
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…
eess.SP2019
Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks
Johanna Rock, Mate Toth, Elmar Messner +2
Driver assistance systems as well as autonomous cars have to rely on sensors to perceive their environment. A heterogeneous set of sensors is used to perform this task robustly. Am…