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Sequential and parallel fusion of detection and classification systems
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Paper Abstract

This paper will investigate the fusion of various detection and classification systems. The architecture of combining these systems is the main interest of this work. We assume the detection and classification systems are known and they are legacy systems such that we know their receiver operating characteristic (ROC) functions, or their approximate ROC functions. Given an objective function we seek the optimal architecture that maximizes the objective function. Combining detection systems sequentially has been around for decades, especially in the bio-medical field where tests are preformed sequentially such that the outcome of one test will determine which test will be performed next. In military applications, we often use multiple detection systems in parallel and combine the outputs into a “fusion” center to determine the final answer. We conjecture that there might be a parallel and series mixture that would yield better performance. Part of determining this mixture is determining which systems go "where" in the mix. We investigate this architecture.

Paper Details

Date Published: 7 May 2019
PDF: 15 pages
Proc. SPIE 11018, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII, 110180G (7 May 2019); doi: 10.1117/12.2518787
Show Author Affiliations
Mark E. Oxley, Air Force Institute of Technology (United States)
Christine M. Schubert-Kabban, Air Force Institute of Technology (United States)

Published in SPIE Proceedings Vol. 11018:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII
Ivan Kadar; Erik P. Blasch; Lynne L. Grewe, Editor(s)

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