BRIC: Bottom-Up Residual Vector Quantization for Learned Image Compression von Flowers, Bryse, Dey, Sujit

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Multi-Source Feature Fusion for Object Detection Association in Connected Vehicle Environments von Thornton, Samuel, Flowers, Bryse, Dey, Sujit

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Countering Physical Eavesdropper Evasion with Adversarial Training von McClintick, Kyle W., Harer, Jacob, Flowers, Bryse, Headley, William C., Wyglinski, Alexander M.

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An RFML Ecosystem: Considerations for the Application of Deep Learning to Spectrum Situational Awareness von Wong, Lauren J., Clark, William H., Flowers, Bryse, Buehrer, R. Michael, Headley, William C., Michaels, Alan J.

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Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications von Flowers, Bryse, Buehrer, R. Michael, Headley, William C.

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Effects of Forward Error Correction on Communications Aware Evasion Attacks von DelVecchio, Matthew, Flowers, Bryse, Headley, William C

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Data from: Multi-Source Feature Fusion for Object Detection Association in Connected Vehicle Environments von Thornton, Samuel, Flowers, Bryse, Dey, Sujit

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Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications von Flowers, Bryse, Buehrer, R. Michael, Headley, William C

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When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions von Sagduyu, Yalin E, Shi, Yi, Erpek, Tugba, Headley, William, Flowers, Bryse, Stantchev, George, Lu, Zhuo

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The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications von Wong, Lauren J, ClarkIV, William H, Flowers, Bryse, Buehrer, R. Michael, Michaels, Alan J, Headley, William C

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Adversarial Machine Learning: A New Threat Paradigm for Next-generation Wireless Communications von Sagduyu, Yalin E., Shi, Yi, Erpek, Tugba, Headley, William, Flowers, Bryse, Stantchev, George, Lu, Zhuo, Jalaian, Brian

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Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications von Flowers, Bryse, Buehrer, R Michael, Headley, William C

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When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions von Sagduyu, Yalin E, Shi, Yi, Erpek, Tugba, Headley, William, Flowers, Bryse, Stantchev, George, Lu, Zhuo

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The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications von Wong, Lauren J, Clark, William H, Flowers, Bryse, Buehrer, R Michael, Michaels, Alan J, Headley, William C

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