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20132026
most citedDistributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors

863 citations · 1.1k across the 19 of their papers we have counts for

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2 papers · 1 filter

eess.SP2019

Crowdsourced wireless spectrum anomaly detection

Sreeraj Rajendran, Vincent Lenders, Wannes Meert +1

Automated wireless spectrum monitoring across frequency, time and space will be essential for many future applications. Manual and fine-grained spectrum analysis is becoming imposs…

eess.SP2018★ 5 cited

SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features

Sreeraj Rajendran, Wannes Meert, Vincent Lenders +1

Detecting anomalous behavior in wireless spectrum is a demanding task due to the sheer complexity of the electromagnetic spectrum use. Wireless spectrum anomalies can take a wide r…