Tony G. Allen

@misc{reid2026SpectralDefense,
  title = {Detection of Adversarial Attacks
                   on Super-Resolvers Using Spectral Features},
  author = {Reid, Emma J. and Duba-Sullivan, Haley and Allen, Tony G.},
  year = {2026},
}

@inproceedings{11674862,
  author = {Story, Mark and Deller, Timothy and Allen, Tony G.},
  booktitle = {2026 IEEE Radar Conference (RadarConf'26)},
  title = {Practical Three-Dimensional Curvilinear Aperture Monopulse Synthetic Aperture Radar},
  year = {2026},
  volume = {},
  number = {},
  pages = {1-6},
  keywords = {Apertures;Printing;Synthetic aperture radar;Equations;Arrays;Specific absorption rate;Radar;Windows;Clouds;Pixel;synthetic aperture radar;monopulse},
  doi = {10.1109/RadarConf2663773.2026.11674862},
}

@misc{tschida2026modalityvsmorphologyframework,
  title = {Modality vs. Morphology: A Framework for Time Series Classification for Biological Signals},
  author = {Tschida, Jordan and Yohe, Matthew and Kane, Edward and Jager, Gavin and Reid, Emma J. and Allen, Tony G. and Story, Mark and Thompson, Leanne and Hoskins, Joe and Schreiber, Brandon and Seiferth, Stan and Dolvin, Scott and Cornett, David},
  year = {2026},
  eprint = {2605.18483},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2605.18483},
}

@techreport{osti_2588947,
  author = {Allen, Tony G. and Duba-Sullivan, Haley and Reid, Emma J.},
  title = {Illuminating the Night: A Survey of Super-Resolution Methods for Nighttime Light Images},
  institution = {Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)},
  annote = {Nighttime Light (NTL) images provide critical insights into urbanization, disaster response, and energy consumption. The VIIRS Day/Night Band (DNB) sensor offers high-quality NTL imagery with daily revisit rates, but the available spatial resolution hinders fine-grained accurate analysis. Super-resolution techniques aim to increase the resolution of NTL images, enabling more detailed assessments of infrastructure, light pollution, economic activity, and power outages. However, existing state-of-the-art super-resolution methods designed for natural images struggle with the unique characteristics of NTL data. This work provides a comprehensive review of super-resolution methods across multiple image modalities, evaluates their effectiveness on VI-IRS DNB data, and proposes a multi-modal super-resolution approach tailored to NTL imagery. The proposed approach integrates VIIRS DNB data with road networks and land use information to improve reconstruction accuracy and spatial detail. Code is available for this project at https://code.ornl.gov/viirs-sr/sr-demos.},
  doi = {10.2172/2588947},
  url = {https://www.osti.gov/biblio/2588947},
  place = {United States},
  year = {2025},
  month = apr,
  data = {https://doi.ccs.ornl.gov/dataset/672823d8-d2c9-5d9d-8a2b-55153849fb89},
}

@article{10910239,
  author = {Allen, Tony G. and Rabb, David J. and Buzzard, Gregery T. and Bouman, Charles A.},
  journal = {IEEE Transactions on Computational Imaging},
  title = {CLAMP: Majorized Plug-and-Play for Coherent 3D Lidar Imaging},
  month = mar,
  year = {2025},
  volume = {11},
  number = {},
  pages = {506-519},
  keywords = {Three-dimensional displays;Laser radar;Imaging;Image reconstruction;Apertures;Speckle;Clamps;Discrete Fourier transforms;Pupils;Chirp;Coherent imaging;consensus equilibrium;deep neural networks;lidar;majorization-minimization;plug-and-play},
  doi = {10.1109/TCI.2025.3548468},
}