Titlebook: Inventive Thinking through TRIZ; A Practical Guide Michael A. Orloff Book 20031st edition Springer-Verlag Berlin Heidelberg 2003 Altshuller

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Michael A. Orloffs in Computer Vision and Pattern Recognition (EMMCVPR2001),whichwasheldatINRIA(InstitutNationaldeRechercheen Informatique et en Automatique) in Sophia Antipolis, France, from September 3 through September 5, 2001. This workshop is the third of a series, which was started with EMMCVPR’97, held in Ven

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Michael A. Orloffces in traditional deformable models come primarily from edges or gradient information and it becomes problematic when the object surfaces have complex large-scale texture patterns that generate many local edges within a same region. We introduce a new textured object segmentation algorithm that has

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Michael A. Orloffally discrete problem. Bayesian approaches to segmentation use priors to impose spatial coherence; the discrete nature of segmentation demands priors defined on discrete-valued fields, thus leading to difficult combinatorial problems..This paper presents a formulation which allows using continuous p

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Book 20031st editiontrophes be avoided? How can we insure the progress and security of coming generations? TRIZ teaches us how to make inventions! TRIZ teaches us how to construct the future! TRIZ changes your thinking, i.e., all of civilization, too! Rational decisions about the problems above cannot be made today wit

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Michael A. Orloffayesian machine learning: introduction of hidden fields to which the region labels are probabilistically related. Since these hidden fields are real-valued, we can adopt any type of spatial prior for continuous-valued fields, such as Gaussian priors. We show how, under this model, Bayesian MAP segme

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Z teaches us how to make inventions! TRIZ teaches us how to construct the future! TRIZ changes your thinking, i.e., all of civilization, too! Rational decisions about the problems above cannot be made today wit978-3-662-08013-9