Abstract
A theoretical approach to the problem of intelligent regulation of data-processing parameters is proposed in terms of joint probability maximization. It is shown that, under suitable hypotheses, the problem can be solved by maximizing, in a distributed way, the product of computationally more tractable conditional probabilities. As a case study, the implementation of an architecture made up of four units is investigated.
This work was carried out and supported within the framework of the MOBIUS project (no. MAST-0028-C), which is included in the CEC MArine Science and Technology (MAST) programme.
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© 1992 Springer-Verlag Berlin Heidelberg
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Murino, V., Peri, M.F., Regazzoni, C.S. (1992). Distributed belief revision for adaptive image processing regulation. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_11
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DOI: https://doi.org/10.1007/3-540-55426-2_11
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