Bayesian truthing and experimental validation in homeland security and defense

Autor: Tomasz Jannson, Andrew A. Kostrzewski, Thomas Forrester, Wenjian Wang, Ranjit Pradhan
Rok vydání: 2014
Předmět:
Zdroj: Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XIII.
ISSN: 0277-786X
DOI: 10.1117/12.2049027
Popis: In this paper we discuss relations between Bayesian Truthing (experimental validation), Bayesian statistics, and Binary Sensing in the context of selected Homeland Security and Intelligence, Surveillance, Reconnaissance (ISR) optical and nonoptical application scenarios. The basic Figure of Merit (FoM) is Positive Predictive Value (PPV), as well as false positives and false negatives. By using these simple binary statistics, we can analyze, classify, and evaluate a broad variety of events including: ISR; natural disasters; QC; and terrorism-related, GIS-related, law enforcement-related, and other C3I events.
Databáze: OpenAIRE