| Machine learning approach to OAM beam demultiplexing via convolutional neural networks T Doster, AT Watnik Applied optics 56 (12), 3386-3396, 2017 | 207 | 2017 |
| Laguerre–Gauss and Bessel–Gauss beams propagation through turbulence: analysis of channel efficiency T Doster, AT Watnik Applied Optics 55 (36), 10239-10246, 2016 | 125 | 2016 |
| 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 | 78 | 2018 |
| 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 | 34 | 2016 |
| 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 | 34 | 2012 |
| Method for free space optical communication utilizing patterned light and convolutional neural networks T Doster, AT Watnik US Patent 10,187,171, 2019 | 30 | 2019 |
| 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 | 28 | 2012 |
| 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 | 19 | 2018 |
| Wavelet packet mixing for image fusion and pan-sharpening W Czaja, T Doster, JM Murphy Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2014 | 17 | 2014 |
| Measuring multiplexed OAM modes with convolutional neural networks T Doster, AT Watnik Applications of Lasers for Sensing and Free Space Communications, LTh3B. 2, 2016 | 14 | 2016 |
| 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 | 14 | 2016 |
| 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 | 13 | 2017 |
| 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 | 13 | 2017 |
| 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 | 12 | 2014 |
| 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 | 11 | 2017 |
| 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 | 10 | 2016 |
| Harmonic analysis inspired data fusion for applications in remote sensing TJ Doster University of Maryland, College Park, 2014 | 9 | 2014 |
| 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 | 8 | 2022 |
| 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 | 7 | 2017 |
| Building robust neighborhoods for manifold learning-based image classification and anomaly detection T Doster, CC Olson Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2016 | 7 | 2016 |
Abbie WatnikNaval Research Laboratory在 nrl.navy.mil 的电子邮件经过验证
