4 citations · 6 across the 2 of their papers we have counts for
2 papers
eess.SP2026★ 2 cited
SMCNet: Supervised Surface Material Classification Using mmWave Radar IQ Signals and Complex-valued CNNs
Stefan Hägele, Fabian Seguel, Driton Salihu +2
Understanding surface material properties is crucial for enhancing indoor robot perception and indoor digital twinning. However, not all sensor modalities typically employed for th…
eess.SP2026★ 4 cited
RadarCNN: Learning-based Indoor Object Classification from IQ Imaging Radar Data
Stefan Hägele, Fabian Seguel, Driton Salihu +2
Radar sensors operating in the mmWave frequency range face challenges when used as indoor perception and imaging devices, primarily due to noise and multipath signal distortions. T…