28 citations · 69 across the 6 of their papers we have counts for
6 papers
An Analysis of RF Transfer Learning Behavior Using Synthetic Data
Lauren J. Wong, Sean McPherson, Alan J. Michaels
Transfer learning (TL) techniques, which leverage prior knowledge gained from data with different distributions to achieve higher performance and reduced training time, are often u…
Assessing the Value of Transfer Learning Metrics for RF Domain Adaptation
Lauren J. Wong, Sean McPherson, Alan J. Michaels
The use of transfer learning (TL) techniques has become common practice in fields such as computer vision (CV) and natural language processing (NLP). Leveraging prior knowledge gai…
Training from Zero: Radio Frequency Machine Learning Data Quantity Forecasting
William H. Clark, Alan J. Michaels
The data used during training in any given application space is directly tied to the performance of the system once deployed. While there are many other factors that go into produc…
The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications
Lauren J. Wong, William H. Clark, Bryse Flowers +3
While deep machine learning technologies are now pervasive in state-of-the-art image recognition and natural language processing applications, only in recent years have these techn…
Training Data Augmentation for Deep Learning Radio Frequency Systems
William H. Clark, Steven Hauser, William C. Headley +1
Applications of machine learning are subject to three major components that contribute to the final performance metrics. Within the category of neural networks, and deep learning s…
Emitter Identification Using CNN IQ Imbalance Estimators
Lauren J. Wong, William C. Headley, Alan J. Michaels
Specific Emitter Identification is the association of a received signal to a unique emitter, and is made possible by the naturally occurring and unintentional characteristics an em…