Alan P. Schaum

发表

Automatic ship detection from commercial multispectral satellite imagery

Eric Allman, Brian J. Daniel, Alan P. Schaum, 2013, Defense, Security, and Sensing.

Hyperspectral change detection in high clutter using elliptically contoured distributions

Eric Allman, Alan P. Schaum, John Kershenstein, 2007, SPIE Defense + Commercial Sensing.

Closed-form solutions to replacement target models of sub-pixel spectral detection

Alan P. Schaum, 2018, Defense + Security.

The affine matched filter

Alan P. Schaum, Richard G. Priest, 2009, Defense + Commercial Sensing.

Multispectral and Hyperspectral Imaging: introduction to the feature issue

John P. Kerekes, Alan P. Schaum, Robert A. Leathers, 2008 .

Spectral ship surveillance from space

Eric Allman, Alan P. Schaum, Robert A. Leathers, 2015, 2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

Next generation signature-based hyperspectral detection: a challenge to atmospheric modelers

Brian J. Daniel, Alan P. Schaum, 2011, Defense + Commercial Sensing.

Clairvoyant Fusion Solutions to Composite Spectral Detection Problems

Alan P. Schaum, 2016 .

Clairvoyant fusion: a new methodology for designing robust detection algorithms

Alan P. Schaum, 2016, Remote Sensing.

Hyperspectral multipass mapping for target detection

Alan P. Schaum, Alan D. Stocker, 2003, SPIE Defense + Commercial Sensing.

Target detection in desert backgrounds: infrared hyperspectral measurements and analysis

Larry B. Stotts, Alan P. Schaum, Craig R. Schwartz, 1995, Optics & Photonics.

Continuum fusion: a new methodology for creating hyperspectral detection algorithms

Alan P. Schaum, 2010, Defense + Commercial Sensing.

Design methods for continuum fusion detectors

Alan P. Schaum, 2011, Defense + Commercial Sensing.

Constructing optimal classifiers from sub-optimal composite hypothesis tests

Alan P. Schaum, 2020, Defense + Commercial Sensing.

Signature evolution with covariance equalization in oblique hyperspectral imagery

Alan P. Schaum, Robert A. Leathers, Trijntje Valerie Downes, 2006, SPIE Defense + Commercial Sensing.

Hyperspectral change detection and supervised matched filtering based on covariance equalization

Alan P. Schaum, Alan D. Stocker, A. Schaum, 2004, SPIE Defense + Commercial Sensing.

Adapting to Change: The CFAR Problem in Advanced Hyperspectral Detection

Alan P. Schaum, 2007, 36th Applied Imagery Pattern Recognition Workshop (aipr 2007).

Advanced hyperspectral detection based on elliptically contoured distribution models and operator feedback

Alan P. Schaum, 2009, 2009 IEEE Applied Imagery Pattern Recognition Workshop (AIPR 2009).

Autonomous Hyperspectral Target Detection with Quasi-Stationarity Violation at Background Boundaries

Alan P. Schaum, 2006, 35th IEEE Applied Imagery and Pattern Recognition Workshop (AIPR'06).

A hyperspectral anomaly detector based on partialing out a clutter subspace

Alan P. Schaum, Edisanter Lo, 2009, Defense + Commercial Sensing.

Invariance concepts in spectral analysis

Alan P. Schaum, 2017, Defense + Security.

The continuum fusion theory of signal detection applied to a bi-modal fusion problem

Alan P. Schaum, 2011, Defense + Commercial Sensing.

Optimal change detection in misregistered image sequences

Alan P. Schaum, 1994, Other Conferences.

Analysis of infrared hyperspectral measurements by the joint multispectral program

Alan P. Schaum, Michael T. Eismann, Alan D. Stocker, 1995, Defense, Security, and Sensing.

Enough with the additive target model

Alan P. Schaum, A. Schaum, 2014, Defense + Security Symposium.

Application of stochastic mixing models to hyperspectral detection problems

Alan P. Schaum, Alan D. Stocker, A. Schaum, 1997, Defense, Security, and Sensing.

CFAR fusion: A replacement for the generalized likelihood ratio test for Neyman-Pearson problems

Alan P. Schaum, A. Schaum, 2011, 2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

Matched affine joint subspace detection in remote hyperspectral reconnaissance

Alan P. Schaum, 2002, Applied Imagery Pattern Recognition Workshop, 2002. Proceedings..

Extending continuum fusion to create unbeatable detectors

Alan P. Schaum, 2013, Defense, Security, and Sensing.

Spectral subspace matched filtering

Alan P. Schaum, A. Schaum, 2001, SPIE Defense + Commercial Sensing.

Linear log-likelihood ratio (L3R) algorithm for spectral target detection

Brian J. Daniel, Alan P. Schaum, 2011, Defense + Commercial Sensing.

Continuum fusion methods of spectral detection

Brian J. Daniel, Alan P. Schaum, A. Schaum, 2012 .

Advanced algorithms for autonomous hyperspectral change detection

Alan A. Stocker, Alan P. Schaum, 2004, 33rd Applied Imagery Pattern Recognition Workshop (AIPR'04).

Bayesian solutions to non-Bayesian detection problems: Unification through fusion

Alan P. Schaum, A. Schaum, 2014, 2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

Subclutter target detection using sequences of thermal infrared multispectral imagery

Alan P. Schaum, Alan D. Stocker, A. Schaum, 1997, Defense, Security, and Sensing.

Target detection enhancement using temporal signature propagation

Alan P. Schaum, Rulon Mayer, 2000, SPIE Defense + Commercial Sensing.

Joint hyperspectral subspace detection derived from a Bayesian likelihood ratio test

Alan P. Schaum, Alan D. Stocker, 2002, SPIE Defense + Commercial Sensing.

Theory and Design of Local Interpolators

Alan P. Schaum, 1993, CVGIP Graph. Model. Image Process..

Urchin: an RX-derivative accounting for anisotropies in whitened clutter

Brian J. Daniel, Alan P. Schaum, 2010, Defense + Commercial Sensing.

Data association for fusion in spatial and spectral imaging

Alan P. Schaum, 2003, 32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings..

Hyperspectral detection algorithms: operational, next generation, on the horizon

Alan P. Schaum, 2005, 34th Applied Imagery and Pattern Recognition Workshop (AIPR'05).

Clairvoyant fusion detection of ocean anomalies in WorldView-2 spectral imagery

Eric Allman, Alan P. Schaum, Matthew Stites, 2016, Optical Engineering + Applications.

Algorithms with attitude

Alan P. Schaum, 2010, 2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR).

Progress in the theory of continuum fusion

Alan P. Schaum, 2012, Defense + Commercial Sensing.