24 citations · 27 across the 6 of their papers we have counts for
4 papers · 1 filter
Large Scale Radio Frequency Wideband Signal Detection & Recognition
Luke Boegner, Garrett Vanhoy, Phillip Vallance +4
Applications of deep learning to the radio frequency (RF) domain have largely concentrated on the task of narrowband signal classification after the signals of interest have alread…
Reservoir Based Edge Training on RF Data To Deliver Intelligent and Efficient IoT Spectrum Sensors
Silvija Kokalj-Filipovic, Paul Toliver, William Johnson +1
Current radio frequency (RF) sensors at the Edge lack the computational resources to support practical, in-situ training for intelligent spectrum monitoring, and sensor data classi…
Practical Fingerprinting of RF Devices in the Wild
Silvija Kokalj-Filipovic, Luke Boegner, Robert D. Miller
We present a new RF fingerprinting technique for wireless emitters that is based on a simple, easily and efficiently retrainable Ridge Regression (RR) classifier. The RR learns to…
Mitigation of Adversarial Examples in RF Deep Classifiers Utilizing AutoEncoder Pre-training
Silvija Kokalj-Filipovic, Rob Miller, Nicholas Chang +1
Adversarial examples in machine learning for images are widely publicized and explored. Illustrations of misclassifications caused by slightly perturbed inputs are abundant and com…