Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing

no code implementations • 19 Jun 2018 • W. Max Lees, Adam Wunderlich, Peter Jeavons, Paul D. Hale, Michael R. Souryal

In this paper, using a library of over 14, 000 3. 5~GHz band spectrograms collected by a recent measurement campaign, we investigate the performance of thirteen methods for SPN-43 radar detection.

BIG-bench Machine Learning Descriptive +1