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Joseph M. Carmack
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2020 – today
- 2022
- [c10]Amit Bhatia, Josh Robinson, Joseph M. Carmack, Scott Kuzdeba:
FPGA Implementation of Radio Frequency Neural Networks. CCWC 2022: 613-618 - [c9]Scott Kuzdeba, Josh Robinson, Joseph M. Carmack, David Couto:
Systems View to Designing RF Fingerprinting for Real-World Operations. WiseML@WiSec 2022: 33-38 - 2021
- [c8]Scott Kuzdeba, Joseph M. Carmack, Josh Robinson:
RF Fingerprinting with Dilated Causal Convolutions-An Inherently Explainable Architecture. ACSCC 2021: 292-299 - [c7]Joseph M. Carmack, Scott Kuzdeba:
RiftNet Reconstruction Model for Radio Frequency Domain Waveform Representation and Synthesis. AIIoT 2021: 303-312 - [c6]Scott Kuzdeba, Josh Robinson, Joseph M. Carmack:
Transfer Learning with Radio Frequency Signals. CCNC 2021: 1-9 - [c5]Josh Robinson, Joseph M. Carmack, Amit Bhatia, John Majewski, Scott Kuzdeba, Joseph Farkas, Brandon Hombs, Thomas Koch:
Neural Network Signal Processing for LTE Receiver Application. DySPAN 2021: 309-314 - [c4]Joseph M. Carmack, Amit Bhatia, Josh Robinson, John Majewski, Scott Kuzdeba:
Neural Network Generative Models for Radio Frequency Data. UEMCON 2021: 577-582 - [c3]Joseph M. Carmack, Steve Schmidt, Scott Kuzdeba:
Multi-Agent Reinforcement Learning Approaches to RF Fingerprint Enhancement. WiseML@WiSec 2021: 67-72 - [c2]Steve Schmidt, James Stankowicz
, Joseph M. Carmack, Scott Kuzdeba:
RiftNeXt™: Explainable Deep Neural RF Scene Classification. WiseML@WiSec 2021: 79-84 - 2020
- [c1]Josh Robinson, Scott Kuzdeba, James Stankowicz
Dilated Causal Convolutional Model For RF Fingerprinting. CCWC 2020: 157-162
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