Wilhelm Stork — accepted AI-conference papers

2020

CNN-Based Lidar Point Cloud De-Noising in Adverse Weather

Robin Heinzler, Florian Piewak, Philipp Schindler, Wilhelm Stork

RA-L 2020

Lidar sensors are frequently used in environment perception for autonomous vehicles and mobile robotics to complement camera, radar, and ultrasonic sensors. Adverse weather conditions are significantly impacting the performance of lidar-based scene understanding by causing undesired measurement poin

Cited by 188 Source ↗code ↗Scholar ↗

2016

Classification of breath and snore sounds using audio data recorded with smartphones in the home environment

Tim Fischer, Johannes Schneider, Wilhelm Stork

ICASSP 2016accepted

In this paper, classification between snore-inhale (SI), snore-exhale (SE), breathe-inhale (BI), breathe-exhale (BE) and noise (NS) sounds is performed. The database is obtained from 7 subjects, who recorded whole night audio data in their private home environments with their own smartphones. Prepro…

Cited by 0 Source ↗Scholar ↗