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5 July 1995 Automatic target recognition via classical detection theory
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Abstract
Classical Bayesian detection and decision theory applies to arbitrary problems with underlying probabilistic models. When the models describe uncertainties in target type, pose, geometry, surround, scattering phenomena, sensor behavior, and feature extraction, then classical theory directly yields detailed model-based automatic target recognition (ATR) techniques. This paper reviews options and considerations arising under a general Bayesian framework for model- based ATR, including approaches to the major problems of acquiring probabilistic models and of carrying out the indicated Bayesian computations.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Douglas R. Morgan "Automatic target recognition via classical detection theory", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); https://doi.org/10.1117/12.213043
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