The project partners develop an innovative approach for energy-efficient artificial intelligence (AI) based on artificial neural networks in Field Programmable Gate Arrays (FPGAs). The aim of the project is to develop a fundamentally new AI structure based on classical CNN architectures for an FPGA using the example of 1-dimensional stream processing (artifact recognition in ECG). With the help of machine learning methods, the signal is evaluated and the result is classified. A given detection rate must be achieved and the energy requirement minimized as far as possible.
Alwyn Burger, Chao Qian, Gregor Schiele, Domenik Helms; 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops); 0March / 2020
Mark Kettner and Behnam Razi Perjikolaei and Wolfgang Nebel; 009 / 2020