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Published in IEEE International Conference on Acoustics, Speech and Signal Processing, 2020
This paper explores a framework for foreground material signature extraction from hyperspectral images based on a proposed patch model.
Recommended citation: J. Hollis, R. Raich, J. Kim, B. Fishbain and S. Kendler, "Foreground Signature Extraction for an Intimate Mixing Model in Hyperspectral Image Classification," ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020, pp. 4732-4736, doi: 10.1109/ICASSP40776.2020.9053456. https://ieeexplore.ieee.org/abstract/document/9053456
Published in IEEE International Conference on Acoustics, Speech and Signal Processing, 2021
This paper proposes the Lead-Class KNN classifier as a defense against high-cost adversarial attacks.
Recommended citation: J. Hollis, J. Kim and R. Raich, "Adversarial Learning via Probabilistic Proximity Analysis," ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, ON, Canada, 2021, pp. 3830-3834, doi: 10.1109/ICASSP39728.2021.9414096. https://ieeexplore.ieee.org/abstract/document/9414096/
Published in IEEE Transactions on Signal Processing, 2024
This paper extends our ICASSP 2020 conference paper, including formal identifiability analysis of the extraction problem and additional algorithms and experiments.
Recommended citation: J. Hollis, R. Raich, J. Kim, B. Fishbain and S. Kendler, "Identifiable Solutions to Foreground Signature Extraction From Hyperspectral Images in an Intimate Mixing Scenario," in IEEE Transactions on Signal Processing, vol. 72, pp. 4081-4097, 2024. https://ieeexplore.ieee.org/document/10541867/
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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