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Probabilistic Solution of Ill-Posed Problems in Computational Vision
699
Zitationen
3
Autoren
1987
Jahr
Abstract
Abstract Computational vision is a set of inverse problems. We review standard regularization theory, discuss its limitations, and present new stochastic (in particular, Bayesian) methods for their solution. We derive efficient algorithms and describe parallel implementations on digital parallel SIMD architectures, as well as a new class of parallel hybrid computers.
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