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NVIDIA presents a demo exploring the RF Spectrum with Deep Learning
June 4 @ 6:00 pm - 8:00 pm
“Exploring the RF Spectrum with Deep Learning” — Adam Thompson
Deep Learning has revolutionized the computer vision domain with many networks now outperforming traditional machine learning and image processing techniques for scene classification and understanding. Can these same ideas, however, be applied to non-imagery data? In this talk, we will highlight the developments and implications of deep learning on RF data – speaking specifically about signal classification, identification, anomaly detection, and scheduling.
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.
THE LOCATION HAS CHANGED! 12750 Fair Lakes Circle · Fairfax, VA (the University of North America has moved!) When you go in the front door go to the elevator on the right behind the front desk and go to floor 1. When you leave the elevator turn left then go straight back. The room number is 1015.
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