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David W. Messinger
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2020 – today
- 2022
- [j8]Sihan Huang, David W. Messinger:
An Unsupervised Cascade Fusion Network for Radiometrically-Accurate Vis-NIR-SWIR Hyperspectral Sharpening. Remote. Sens. 14(17): 4390 (2022) - [j7]Sihan Huang, David W. Messinger:
An Unsupervised Laplacian Pyramid Network for Radiometrically Accurate Data Fusion of Hyperspectral and Multispectral Imagery. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c21]Morteza Maali Amiri, David W. Messinger:
Virtual Cleaning of Artworks Usinga Deep Generative Network. CVCS 2022 - [i2]William Basener, Alexey Castrodad, David W. Messinger, Jennifer Mahle, Paul Prue:
A Dynamical Systems Algorithm for Clustering in Hyperspectral Imagery. CoRR abs/2207.10625 (2022) - 2021
- [j6]Anna Starynska, David W. Messinger, Yu Kong:
Revealing a history: palimpsest text separation with generative networks. Int. J. Document Anal. Recognit. 24(3): 181-195 (2021) - [j5]Tania Kleynhans, David W. Messinger, Roger L. Easton Jr., John K. Delaney:
Low-Cost Multispectral System Design for Pigment Analysis in Works of Art. Sensors 21(15): 5138 (2021) - [i1]Abu Md Niamul Taufique, David W. Messinger:
Hyperspectral Pigment Analysis of Cultural Heritage Artifacts Using the Opaque Form of Kubelka-Munk Theory. CoRR abs/2104.04884 (2021) - 2020
- [c20]Di Bai, David W. Messinger, David Howell:
Deep Learning Spatial-Spectral Processing of Hyperspectral Images for Pigment Mapping of Cultural Heritage Artifacts. ICPR Workshops (7) 2020: 200-214
2010 – 2019
- 2018
- [j4]Michal Kucer, Alexander C. Loui, David W. Messinger:
Leveraging Expert Feature Knowledge for Predicting Image Aesthetics. IEEE Trans. Image Process. 27(10): 5100-5112 (2018) - [c19]Michal Kucer, David W. Messinger:
Aesthetic Inference for Smart Mobile Devices. WACV 2018: 1764-1773 - 2017
- [j3]Jeffrey R. Stevens, Ronald G. Resmini, David W. Messinger:
Spectral-Density-Based Graph Construction Techniques for Hyperspectral Image Analysis. IEEE Trans. Geosci. Remote. Sens. 55(10): 5966-5983 (2017) - [c18]Michal Kucer, Nathan D. Cahill, Alexander C. Loui, David W. Messinger:
Augmenting Salient Foreground Detection using Fiedler Vector for Multi-Object Segmentation. Computational Imaging 2017: 116-121 - [c17]Anna Starynska, Roger L. Easton Jr., David W. Messinger:
Methods of data augmentation for palimpsest character recognition with Deep Neural Network. HIP@ICDAR 2017: 54-58 - [c16]Leidy P. Dorado-Muñoz, David W. Messinger:
Global and adaptive K-nearest neighbor graphs in a spectral target detector based on Schroedinger Eigenmaps. IGARSS 2017: 1336-1339 - 2015
- [c15]Amanda K. Ziemann, James Theiler, David W. Messinger:
Hyperspectral target detection using manifold learning and multiple target spectra. AIPR 2015: 1-7 - [c14]Yang Hu, Eli Saber, Sildomar T. Monteiro, Nathan D. Cahill, David W. Messinger:
Classification of hyperspectral images based on conditional random fields. Image Processing: Machine Vision Applications 2015: 940510 - 2014
- [c13]Jordyn Stoddard, David W. Messinger, John P. Kerekes:
Effects of cubesat design parameters on image quality and feature extraction for 3D reconstruction. IGARSS 2014: 1995-1998 - [c12]Amanda K. Ziemann, David W. Messinger:
Manifold representations of single and multiple material classes in high resolution HSI. WHISPERS 2014: 1-4 - 2013
- [c11]James A. Albano, Amanda K. Ziemann, David W. Messinger:
Assessing the impact of the edge-weighting function in a graph-based approach to anomaly detection. WHISPERS 2013: 1-4 - [c10]Maria Busuioceanu, David W. Messinger, John Greer, Christopher Flake:
Analysis and utility of atmospheric compensation of simulated compressive sensing (CS) measurements. WHISPERS 2013: 1-4 - 2012
- [j2]Ariel Schlamm, David W. Messinger, William Basener:
Interest Segmentation of Large Area Spectral Imagery for Analyst Assistance. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 5(2): 409-420 (2012) - [c9]Kelly Canham, Nina G. Raqueno, William Middleton, David W. Messinger:
Comparison of hyperion spectral unmixing endmembers to material spectral profiles from Oaxaca, Mexico. IGARSS 2012: 4114-4117 - 2011
- [j1]Kelly Canham, Ariel Schlamm, Amanda Ziemann, Bill Basener, David W. Messinger:
Spatially Adaptive Hyperspectral Unmixing. IEEE Trans. Geosci. Remote. Sens. 49(11): 4248-4262 (2011) - [c8]Sreenath Rao Vantaram, Eli Saber, David W. Messinger:
An intensity-gradient-texture guided methodology for spatial segmentation of remotely sensed multi/hyperspectral imagery. ICIP 2011: 2885-2888 - [c7]Bill Basener, Ariel Schlamm, David W. Messinger, Emmett J. Ientilucci:
A detection-identification process with geometric target detection and subpixel spectral visualization. WHISPERS 2011: 1-4 - [c6]Ryan A. Mercovich, James Albano, David W. Messinger:
Techniques for the graph representation of spectral imagery. WHISPERS 2011: 1-4 - [c5]David W. Messinger, James Albano:
A graph theoretic approach to anomaly detection in hyperspectral imagery. WHISPERS 2011: 1-4 - [c4]Ariel Schlamm, David W. Messinger:
Improved detection and clustering of hyperspectral image data by preprocessing with a euclidean distance transformation. WHISPERS 2011: 1-4 - 2010
- [c3]David W. Messinger, Amanda Ziemann, Ariel Schlamm, Bill Basener:
Spectral image complexity estimated through local convex hull volume. WHISPERS 2010: 1-4 - [c2]Ariel Schlamm, David W. Messinger, William Basener:
Interest segmentation of hyperspectral imagery. WHISPERS 2010: 1-4
2000 – 2009
- 2006
- [c1]David W. Messinger, Jason E. West, John R. Schott:
Improving Background Multivariate Normality and Target Detection Performance using Spatial and Spectral Segmentation. IGARSS 2006: 371-374
Coauthor Index
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