Paper
18 September 1998 Spatial scan density estimates
Carey E. Priebe, Dalei Chen
Author Affiliations +
Abstract
The detection and identification of regions of interest in spatial or temporal data is a common concern in automatic target recognition. One approach to region of interest identification involves the use of spatial scan statistics. A difficulty arises due to competing concerns: small scan windows are required for potentially small targets while larger scan windows are necessary to improve the accuracy of the detector. When the scan statistics are mixture model density estimates, a borrowed strength profile likelihood approach can be shown to be superior to conventional likelihood estimators.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Carey E. Priebe and Dalei Chen "Spatial scan density estimates", Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); https://doi.org/10.1117/12.323849
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KEYWORDS
Expectation maximization algorithms

Statistical analysis

Error analysis

Automatic target recognition

Monte Carlo methods

Evolutionary algorithms

Unmanned aerial vehicles

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