Signal Processing and Speech Communication Laboratory
homephd theses › Deep Learning for Resource-Constrained Radar Systems

Deep Learning for Resource-Constrained Radar Systems

In work
Johanna Rock
Franz Pernkopf
Research Areas

Radar systems provide information about object distances, velocities and positions but they can also be used for object recognition, such as pedestrian classification. The constant sensing of the various sensors in a car produces a huge amount of raw data, which requires an intelligent extraction of relevant data as well as distributed processing on the sensing units themselves. In this project we investigate the use of machine learning methods such as Deep Neural Networks to address these issues. Special attention is placed on resource efficiency of the used models in order to deploy them directly to the hardware.