Follow
Timothy Doster
Title
Cited by
Cited by
Year
Machine learning approach to OAM beam demultiplexing via convolutional neural networks
T Doster, AT Watnik
Applied optics 56 (12), 3386-3396, 2017
2172017
Laguerre–Gauss and Bessel–Gauss beams propagation through turbulence: analysis of channel efficiency
T Doster, AT Watnik
Applied Optics 55 (36), 10239-10246, 2016
1312016
De-multiplexing vortex modes in optical communications using transport-based pattern recognition
SR Park, L Cattell, JM Nichols, A Watnik, T Doster, GK Rohde
Optics express 26 (4), 4004-4022, 2018
812018
Gradual DropIn of Layers to Train Very Deep Neural Networks
LN Smith, EM Hand, T Doster
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4763-4771, 2016
382016
Semi-supervised learning of heterogeneous data in remote sensing imagery
J Benedetto, W Czaja, J Dobrosotskaya, T Doster, K Duke, D Gillis
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net …, 2012
342012
Method for free space optical communication utilizing patterned light and convolutional neural networks
T Doster, AT Watnik
US Patent 10,187,171, 2019
312019
Integration of heterogeneous data for classification in hyperspectral satellite imagery
J Benedetto, W Czaja, J Dobrosotskaya, T Doster, K Duke, D Gillis
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2012
292012
Transport-based model for turbulence-corrupted imagery
JM Nichols, TH Emerson, L Cattell, S Park, A Kanaev, F Bucholtz, ...
Applied optics 57 (16), 4524-4536, 2018
192018
Wavelet packet mixing for image fusion and pan-sharpening
W Czaja, T Doster, JM Murphy
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2014
172014
Measuring multiplexed OAM modes with convolutional neural networks
T Doster, AT Watnik
Applications of Lasers for Sensing and Free Space Communications, LTh3B. 2, 2016
152016
In what ways are deep neural networks invariant and how should we measure this?
H Kvinge, T Emerson, G Jorgenson, S Vasquez, T Doster, J Lew
Advances in Neural Information Processing Systems 35, 32816-32829, 2022
142022
The pre-image problem for Laplacian eigenmaps utilizing l1 regularization with applications to data fusion
A Cloninger, W Czaja, T Doster
Inverse Problems 33 (7), 074006, 2017
142017
A parametric study of unsupervised anomaly detection performance in maritime imagery using manifold learning techniques
CC Olson, T Doster
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2016
142016
A novel detection paradigm and its comparison to statistical and kernel-based anomaly detection algorithms for hyperspectral imagery
CC Olson, T Doster
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
132017
Operator analysis and diffusion based embeddings for heterogeneous data fusion
A Cloninger, W Czaja, T Doster
2014 IEEE Geoscience and Remote Sensing Symposium, 1249-1252, 2014
132014
Spatial-spectral operator theoretic methods for hyperspectral image classification
JJ Benedetto, W Czaja, J Dobrosotskaya, T Doster, K Duke
GEM-International Journal on Geomathematics 7, 275-297, 2016
122016
An optimal transport model for imaging in atmospheric turbulence
JM Nichols, AT Watnik, T Doster, S Park, A Kanaev, L Cattell, GK Rohde
arXiv preprint arXiv:1705.01050, 2017
112017
Harmonic analysis inspired data fusion for applications in remote sensing
TJ Doster
University of Maryland, College Park, 2014
102014
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, ...
Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing …, 2014
82014
A study of anomaly detection performance as a function of relative spectral abundances for graph-and statistics-based detection algorithms
CC Olson, M Coyle, T Doster
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2017
72017
The system can't perform the operation now. Try again later.
Articles 1–20