Peak effect and scaling of irreversible properties in untwinned Y-Ba-Cu-O crystals.
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Biomedical subjects
Publications and source records attributed to Y Yeshurun.
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Symmetry is one of the most prominent cues in visual perception as well as in computer vision. We have recently presented a Generalized Symmetry Transform that receives as input an edge map, and outputs a symmetry map, where every point marks the intensity and orientation of the local generalized symmetry. In the context of computer vision, this map emphasizes points of high symmetry, which, in turn, are used to detect regions of interest for active vision systems. Many psychophysical experiments in texture discrimination use images that consist of various micro-patterns. Since the Generalized Symmetry Transform captures local spatial relations between image edges, it has been used here to predict human performance in discrimination tasks. Applying the transform to micro-patterns in some well-studied quantitative experiments of human texture discrimination, it is shown that symmetry, as characterized by the present computational scheme, can account for most of them.
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The convoluted form of the sheet-like mammalian cortex naturally raises the question whether there is a simple geometrical reason for the prevalence of cortical architecture in the brains of higher vertebrates. Addressing this question, we present a formal analysis of the volume occupied by a massively connected network or processors (neurons) and then consider the pertaining cortical data. Three gross macroscopic features of cortical organization are examined: the segregation of white and gray matter, the circumferential organization of the gray matter around the white matter, and the folded cortical structure. Our results testify to the efficiency of cortical architecture.
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