D. Gillis

发表

Manifold learning techniques for the analysis of hyperspectral ocean data

M. Montes, C. Bachmann, T. Ainsworth, 2005 .

Semi-supervised learning of heterogeneous data in remote sensing imagery

John J. Benedetto, David Gillis, Timothy Doster, 2012, Defense + Commercial Sensing.

Airborne system for multispectral, multiangle polarimetric imaging.

Deric J Gray, Jeffrey H Bowles, Marcos J Montes, 2015, Applied optics.

High spatial resolution spectrometry of rafting macroalgae (Sargassum)

David Gillis, Jeffrey H. Bowles, George O. Marmorino, 2010 .

An Introduction to Hyperspectral Image Data Modeling

David Gillis, Jeffrey H. Bowles, J. Bowles, 2013 .

Bathymetric Retrieval From Hyperspectral Imagery Using Manifold Coordinate Representations

Thomas L. Ainsworth, Daniel Korwan, Marcos J. Montes, 2009, IEEE Transactions on Geoscience and Remote Sensing.

ORASIS framework - benefits to working within the linear mixing model

Jeffrey H. Bowles, Wei Chen, David Gillis, 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

Target detection in hyperspectral imagery using demixed spectral angles

David Gillis, Jeffrey H. Bowles, J. Bowles, 2004, SPIE Remote Sensing.

Using endmembers as a coordinate system in hyperspectral imagery

David Gillis, Jeffrey H. Bowles, Michael E. Winter, 2002, SPIE Optics + Photonics.

Automatic target-recognition system for hyperspectral imagery using ORASIS

David Gillis, Jeffrey H. Bowles, Peter J. Palmadesso, 2001, SPIE Defense + Commercial Sensing.

Deriving bathymetry and water properties from hyperspectral imagery by spectral matching using a full radiative transfer model

M. Montes, J. Bowles, W. D. Miller, 2020 .

An Underwater Target Detection Framework for Hyperspectral Imagery

David B. Gillis, D. Gillis, 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Improving the retrieval of water inherent optical properties in noisy hyperspectral data through statistical modeling.

Wesley J Moses, David B Gillis, Jeffrey H Bowles, 2013, Optics express.

A new data-driven approach to modeling coastal bathymetry from hyperspectral imagery using manifold coordinates

M. Montes, C. Bachmann, T. Ainsworth, 2005, Proceedings of OCEANS 2005 MTS/IEEE.

Propagation of sensor noise in oceanic hyperspectral remote sensing.

Wesley J Moses, Jeffrey H Bowles, Marcos J Montes, 2018, Optics express.

New improvements in the ORASIS algorithm

David Gillis, Jeffrey H. Bowles, Peter J. Palmadesso, 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

Error analysis in hyperspectral unmixing

David Gillis, Jeffrey H. Bowles, J. Bowles, 2004, SPIE Defense + Commercial Sensing.

Dimensionality reduction in hyperspectral imagery

David Gillis, Jeffrey H. Bowles, Michael E. Winter, 2003, SPIE Defense + Commercial Sensing.

Retrieval of Substrate Bearing Strength from Hyperspectral Imagery during the Virginia Coast Reserve (VCR’07) Multi-Sensor Campaign

W. David Miller, Ellen Bennert, Daniel Korwan, 2010 .

Interpretation of Absorption Bands in Airborne Hyperspectral Radiance Data

W. David Miller, David B. Gillis, Jeffrey H. Bowles, 2009, Sensors.

Integration of heterogeneous data for classification in hyperspectral satellite imagery

John J. Benedetto, David Gillis, Timothy Doster, 2012, Defense + Commercial Sensing.

Change detection using mean-shift and outlier-distance metrics

Ariel Schlamm, David W. Messinger, David Gillis, 2011, Defense + Commercial Sensing.

Improving the retrieval of water inherent optical properties in noisy hyperspectral data through statistical modeling.

W. Moses, J. Bowles, D. Gillis, 2013, Optics express.

Automated identification of components in a chemical mixture utilizing multi‐wavelength resonant‐Raman spectroscopy and a Pearson correlation algorithm

C. Manka, J. Grun, J. Bowles, 2012 .

A generalized linear mixing model for hyperspectral imagery

David W. Messinger, Emmett J. Ientilucci, David Gillis, 2008, SPIE Defense + Commercial Sensing.

Exploiting nonlinear structure in hyperspectral coastal data

David Gillis, Jeffrey H. Bowles, Ellen Bennert, 2006, SPIE Optics + Photonics.