Lauren J. Wong

According to our database, Lauren J. Wong authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Assessing the Value of Transfer Learning Metrics for Radio Frequency Domain Adaptation.

Lauren J. Wong, Braeden P. Muller, Sean McPherson, Alan J. Michaels

Mach. Learn. Knowl. Extr., September, 2024

Transferring Learned Behaviors between Similar and Different Radios.

Braeden P. Muller, Brennan E. Olds, Lauren J. Wong, Alan J. Michaels

Sensors, June, 2024

An Analysis of Radio Frequency Transfer Learning Behavior.

Lauren J. Wong, Braeden P. Muller, Sean McPherson, Alan J. Michaels

Mach. Learn. Knowl. Extr., June, 2024

Sensitivity Analysis of RFML Applications.

Braeden P. Muller, Lauren J. Wong, Alan J. Michaels

IEEE Access, 2024

2023

A Real-World Dataset Generator for Specific Emitter Identification.

Braeden P. Muller, Lauren J. Wong, William H. Clark, Alan J. Michaels

IEEE Access, 2023

2022

Transfer Learning for RF Domain Adaptation - Synthetic Dataset.

Lauren J. Wong, Sean McPherson, Alan J. Michaels

Dataset, March, 2022

Transfer Learning for Radio Frequency Machine Learning: A Taxonomy and Survey.

Lauren J. Wong, Alan J. Michaels

Sensors, 2022

Quantifying Raw RF Dataset Similarity for Transfer Learning Applications.

Lauren J. Wong, Sean McPherson, Alan J. Michaels

IEEE Open J. Commun. Soc., 2022

Classification of Radio Signals Using Truncated Gaussian Discriminant Analysis of Convolutional Neural Network-Derived Features.

J. B. Persons, Lauren J. Wong, Megan O. Moore, William C. Headley, Michael Fowler

Proceedings of the IEEE Military Communications Conference, 2022

2021

An RFML Ecosystem: Considerations for the Application of Deep Learning to Spectrum Situational Awareness.

Lauren J. Wong, William H. Clark, Bryse Flowers, R. Michael Buehrer, William C. Headley, Alan J. Michaels

IEEE Open J. Commun. Soc., 2021

Multinomial-Based Decision Synthesis of ML Classification Outputs.

Alan J. Michaels, Lauren J. Wong

Proceedings of the Modeling Decisions for Artificial Intelligence, 2021

Explainable Neural Network-based Modulation Classification via Concept Bottleneck Models.

Lauren J. Wong, Sean McPherson

Proceedings of the 11th IEEE Annual Computing and Communication Workshop and Conference, 2021

2020

Resilience Improvements for Space-Based Radio Frequency Machine Learning.

Lauren J. Wong, Emily Altland, Joshua Detwiler, Paolo Fermin, Julia Mahon Kuzin, Nathan Moeliono, Abdelrahman Said Abdalla, William C. Headley, Alan J. Michaels

Proceedings of the 2020 International Symposium on Networks, Computers and Communications, 2020

2019

Groundwork for Neural Network-Based Specific Emitter Identification Authentication for IoT.

Jason M. McGinthy, Lauren J. Wong, Alan J. Michaels

IEEE Internet Things J., 2019

Specific Emitter Identification Using Convolutional Neural Network-Based IQ Imbalance Estimators.

Lauren J. Wong, William C. Headley, Alan J. Michaels

IEEE Access, 2019

Distributed Automatic Modulation Classification with Compressed Data.

Lauren J. Wong, Parker D. White, Michael Fowler, William C. Headley

Proceedings of the 2019 IEEE Military Communications Conference, 2019

Developing RFML Intuition: An Automatic Modulation Classification Architecture Case Study.

William H. Clark, Vanessa Arndorfer, Brook Tamir, Daniel Kim, Cristian Vives, Hunter Morris, Lauren J. Wong, William C. Headley

Proceedings of the 2019 IEEE Military Communications Conference, 2019

2018

Clustering Learned CNN Features from Raw I/Q Data for Emitter Identification.

Lauren J. Wong, William C. Headley, Seth Andrews, Ryan M. Gerdes, Alan J. Michaels

Proceedings of the 2018 IEEE Military Communications Conference, 2018

Estimation of transmitter I/Q imbalance using convolutional neural networks.

Lauren J. Wong, William C. Headley, Alan J. Michaels

Proceedings of the IEEE 8th Annual Computing and Communication Workshop and Conference, 2018