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16 August 2001 User-defined information and scientific performance evaluation
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For the past two years at this conference we have described results in the practical implementation of a unified, scientific approach to performance measurement for data fusion algorithms. Our approach is based on finite set statistics (FISST), a generalization of conventional statistics to multisource, multitarget problems. Finite-set statistics makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems in such a way that information can be defined and measured even though any given end-user may have conflicting or even subjective definitions of what information means. In this follow-on paper we describe the performance of FISST based metrics that take into account a user's definition of information and develop a rigorous theory of partial information for multisource, multi-target problems.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John R. Hoffman, Ronald P. S. Mahler, and Tim Zajic "User-defined information and scientific performance evaluation", Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001);


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