Dr. Timothy J. Doster Profile

Dr. Timothy J. Doster

at Pacific Northwest National Lab

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Author

Publications (15)

Proceedings Article | 8 June 2024 Poster

Towards joint estimation of bathymetry and water-column-corrected spectra with neural ODEs

Luis Cedillo, James Koch, Timothy Doster, Tegan Emerson

Proceedings Volume 13031, 130310T (2024) https://doi.org/10.1117/12.3014333

KEYWORDS: Machine learning, Radiative transfer, Ordinary differential equations, Modeling, LIDAR, Hyperspectral imaging, Ecosystems

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Proceedings Article | 8 June 2024 Presentation

Adapting self-supervised learning to the hyperspectral domain: methods, challenges, and lessons learned

Noriaki Kono, Eleanor Byler, Charles Godfrey, Timothy Doster, Tegan Emerson

Proceedings Volume 13031, 130310J (2024) https://doi.org/10.1117/12.3013487

KEYWORDS: Performance modeling, Data modeling, Library classification systems, Hyperspectral imaging, Deep learning, Computer vision technology

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Proceedings Article | 13 June 2023 Presentation + Paper

A neural differential equation formulation for modeling atmospheric effects in hyperspectral images

James Koch, Brenda Forland, Timothy Doster, Tegan Emerson

Proceedings Volume 12519, 125190E (2023) https://doi.org/10.1117/12.2663958

KEYWORDS: Atmospheric modeling, Atmospheric corrections, Atmospheric physics, Machine learning, Modeling, Physics, Differential equations, Artificial intelligence

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Proceedings Article | 6 June 2022 Poster + Paper

To fail or not to fail: an exploration of machine learning techniques for predictive maintenance

Samuel Dixon, Timothy Doster, Tegan Emerson

Proceedings Volume 12113, 1211320 (2022) https://doi.org/10.1117/12.2619040

KEYWORDS: Failure analysis, Analytical research, Visualization, Data modeling, Principal component analysis, Machine learning, Sensors, Detection and tracking algorithms, Statistical analysis, Particles

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Proceedings Article | 17 May 2018 Paper

A study of the effect of alternative similarity measures on the performance of graph-based anomaly detection algorithms

T. Emerson, C. Olson, T. Doster

Proceedings Volume 10644, 106440F (2018) https://doi.org/10.1117/12.2306090

KEYWORDS: Data modeling, Detection and tracking algorithms, Distance measurement, Statistical modeling, Sensors, Principal component analysis, Algorithm development, Hyperspectral imaging, Target detection, Matrices

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Proceedings Article | 8 May 2018 Paper

Kernel PCA for anomaly detection in hyperspectral images using spectral-spatial fusion

R. Meinhold, C. Olson, T. Doster

Proceedings Volume 10644, 1064427 (2018) https://doi.org/10.1117/12.2306359

KEYWORDS: Data modeling, Image fusion, Hyperspectral imaging, Principal component analysis, Multispectral imaging, Data fusion, Detection and tracking algorithms

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Proceedings Article | 19 July 2017 Paper

A study of anomaly detection performance as a function of relative spectral abundances for graph- and statistics-based detection algorithms

C. Olson, M. Coyle, T. Doster

Proceedings Volume 10198, 101980X (2017) https://doi.org/10.1117/12.2264160

KEYWORDS: Statistical analysis, Detection and tracking algorithms, Statistical modeling, Error analysis

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Proceedings Article | 5 May 2017 Paper

Designing manufacturable filters for a 16-band plenoptic camera using differential evolution

Timothy Doster, Colin Olson, Erin Fleet, Michael Yetzbacher, Andrey Kanaev, Paul Lebow, Robert Leathers

Proceedings Volume 10198, 1019803 (2017) https://doi.org/10.1117/12.2262574

KEYWORDS: Optical filters, Target detection, Cameras, Compressed sensing, Hyperspectral target detection, Design for manufacturability, Image filtering, Imaging systems, Optimization (mathematics), Bandpass filters, Computational imaging, Multispectral imaging

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Proceedings Article | 25 May 2016 Paper

A parametric study of unsupervised anomaly detection performance in maritime imagery using manifold learning techniques

C. Olson, T. Doster

Proceedings Volume 9840, 984016 (2016) https://doi.org/10.1117/12.2227226

KEYWORDS: Data modeling, Statistical modeling, Detection and tracking algorithms, Target detection, Target detection, Detection and tracking algorithms, Principal component analysis, Solids, Error analysis, Infrared imaging, Infrared radiation, Sensors

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Proceedings Article | 25 May 2016 Paper

Building robust neighborhoods for manifold learning-based image classification and anomaly detection

Timothy Doster, Colin Olson

Proceedings Volume 9840, 984015 (2016) https://doi.org/10.1117/12.2227224

KEYWORDS: Image classification, Distance measurement, Sensors, Image analysis, Image processing, Algorithm development, Detection and tracking algorithms, Neodymium, Dimension reduction, Infrared imaging

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Proceedings Article | 13 June 2014 Paper

Wavelet packet mixing for image fusion and pan-sharpening

Wojciech Czaja, Timothy Doster, James Murphy

Proceedings Volume 9088, 908803 (2014) https://doi.org/10.1117/12.2050405

KEYWORDS: Wavelets, Image fusion, Spatial resolution, Data fusion, Image compression, Neodymium, RGB color model, Multispectral imaging, Image quality, Earth observing sensors

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Proceedings Article | 29 May 2014 Paper

Operator based integration of information in multimodal radiological search mission with applications to anomaly detection

J. Benedetto, A. Cloninger, W. Czaja, T. Doster, K. Kochersberger, B. Manning, T. McCullough, M. McLane

Proceedings Volume 9073, 90731A (2014) https://doi.org/10.1117/12.2050721

KEYWORDS: Gamma radiation, Information fusion, Target detection, Sensors, Data acquisition, Spatial analysis, Machine learning, Radon, Signal detection, Integration

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Proceedings Article | 24 May 2012 Paper

Integration of heterogeneous data for classification in hyperspectral satellite imagery

J. Benedetto, W. Czaja, J. Dobrosotskaya, T. Doster, K. Duke, D. Gillis

Proceedings Volume 8390, 839027 (2012) https://doi.org/10.1117/12.919236

KEYWORDS: Hyperspectral imaging, Data integration, Data fusion, Sensors, Satellite imaging, Earth observing sensors, Satellites, Analytical research, Target detection, Control systems

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Proceedings Article | 10 May 2012 Paper

Semi-supervised learning of heterogeneous data in remote sensing imagery

J. Benedetto, W. Czaja, J. Dobrosotskaya, T. Doster, K. Duke, D. Gillis

Proceedings Volume 8401, 840104 (2012) https://doi.org/10.1117/12.919259

KEYWORDS: Hyperspectral imaging, Analytical research, Control systems, Remote sensing, Digital imaging, Machine learning, Sensors, Radon, Multispectral imaging, Principal component analysis

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Proceedings Article | 27 April 2009 Paper

Anomaly clustering in hyperspectral images

Timothy Doster, David Ross, David Messinger, William Basener

Proceedings Volume 7334, 73341P (2009) https://doi.org/10.1117/12.818407

KEYWORDS: Hyperspectral imaging, Detection and tracking algorithms, Statistical analysis, Visualization, Algorithm development, Mathematical modeling, Multispectral imaging, Image analysis, Buildings, Image processing

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Showing 5 of 15 publications

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