Optimization of Automatic Target Recognition with a Reject Option Using Fusion and Correlated Sensor Data - Tapa blanda

Laine, Trevor I.

 
9781249836100: Optimization of Automatic Target Recognition with a Reject Option Using Fusion and Correlated Sensor Data
Tapa blanda
ISBN 10: 1249836107 ISBN 13: 9781249836100
Editorial: BiblioScholar, 2012

Sinopsis

This dissertation research makes contributions toward the optimization of automatic target recognition (ATR) systems when a rejection option is included. First, a comprehensive review of the literature inclusive of ATR assessment, fusion, correlated sensor data, and classifier rejection is presented. An optimization framework for the fusion of multiple sensors is then developed. This framework identifies preferred fusion rules and sensors along with rejection and receiver operating characteristic (ROC) curve thresholds without the use of explicit misclassification costs as required by a Bayes' loss function. This optimization framework is the first to integrate both vertical warfighter output label analysis and horizontal engineering confusion matrix analysis. In addition, optimization is performed for the true positive rate, which incorporates the time required by classification systems. The mathematical programming framework is used to assess different fusion methods and to characterize correlation effects both within and across sensors.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

This dissertation research makes contributions toward the optimization of automatic target recognition (ATR) systems when a rejection option is included. First, a comprehensive review of the literature inclusive of ATR assessment, fusion, correlated sensor data, and classifier rejection is presented. An optimization framework for the fusion of multiple sensors is then developed. This framework identifies preferred fusion rules and sensors along with rejection and receiver operating characteristic (ROC) curve thresholds without the use of explicit misclassification costs as required by a Bayes' loss function. This optimization framework is the first to integrate both vertical warfighter output label analysis and horizontal engineering confusion matrix analysis. In addition, optimization is performed for the true positive rate, which incorporates the time required by classification systems. The mathematical programming framework is used to assess different fusion methods and to characterize correlation effects both within and across sensors.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
BiblioScholar
Año de publicación
2012
Idioma
Inglés
ISBN 10 
1249836107
ISBN 13 
9781249836100
Encuadernación
Tapa blanda
Número de páginas
334
Contacto del fabricante
no disponible
Persona responsable
no disponible