FR4.R13.1

LINEAR MIXING MODEL PERFORMANCE WITH NONLINEAR EFFECTS IN HYPERSPECTRAL SUB-PIXEL TARGET DETECTION

Colin J. Maloney, John P. Kerekes, Emmett J. Ientilucci, Chase Canas, Rochester Institute of Technology, United States
Session:
FR4.R13: Rare Target Detection in Spectral Imagery II Oral
Track:
Community-Contributed Sessions
Location:
Room 105
Presentation Time:
Fri, 21 Jul, 15:45 - 15:57 Pacific Time (UTC -7)
Session Co-Chairs:
Stanley Rotman, Ben-Gurion University of the Negev and Stefania Matteoli, National Research Council of Italy (CNR)
Session Manager:
Shankho Subhra Pal
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Session FR4.R13
FR4.R13.1: LINEAR MIXING MODEL PERFORMANCE WITH NONLINEAR EFFECTS IN HYPERSPECTRAL SUB-PIXEL TARGET DETECTION
Colin J. Maloney, John P. Kerekes, Emmett J. Ientilucci, Chase Canas, Rochester Institute of Technology, United States
FR4.R13.2: IMPACTS OF FULLY ILLUMINATED TARGETS ON PARTIALLY SHADED BACKGROUNDS FOR A MULTICLASS SUBPIXEL TARGET DETECTION SCENARIO
Chase Cañas, John Kerekes, Colin Maloney, Emmett Ientilucci, Scott Brown, Rochester Institute of Technology, United States
FR4.R13.3: OPTIONS FOR SOLID POINT TARGET DETECTION IN HYPERSPECTRAL DATA
Eliad Yorkovetsky, Stanley Rotman, Ben-Gurion University of the Negev, Israel
FR4.R13.4: CLOSED-FORM NON-PARAMETRIC ADMISSIBLE DETECTOR FOR SOLID SUB-PIXEL TARGETS
Stefania Matteoli, National Research Council of Italy (CNR), Italy; James Theiler, Los Alamos National Laboratory, United States
FR4.R13.5: BAYESIAN VS GENERALIZED LIKELIHOOD RATIO DETECTION OF SOLID SUB-PIXEL TARGETS
James Theiler, Los Alamos National Laboratory, United States
Resources
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