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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 334. Bestandsnummer des Verkäufers 26393273573
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand pp. 334. Bestandsnummer des Verkäufers 386359098
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND pp. 334. Bestandsnummer des Verkäufers 18393273583
Anzahl: 4 verfügbar
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
Paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA79612498361076
Anzahl: 1 verfügbar