50 research outputs found

    Inheritance of Resistance to Six Races of Bunt, to Awns and Kernel Color in a Wheat Cross

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    Wheat is the most important cereal crop of the world, and one of the most serious diseases affecting it over much of its range is covered smut or bunt (57). The word bunt , according to Heald (48), is a contraction of an old English term, burnt ear , which fittingly describes the ravages of covered smut

    A Mixed Length Scale Model for Migrating Fluvial Bedforms

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    Does a Plane Imitate a Bird? Does Computer Vision Have to Follow Biological Paradigms?

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    We posit a new paradigm for image information processing. For the last 25 years, this task was usually approached in the frame of Triesman's twostage paradigm [1]. The latter supposes an unsupervised, bottom-up directed process of preliminary information pieces gathering at the lower processing stages and a supervised, top-down directed process of information pieces binding and grouping at the higher stages. It is acknowledged that these subprocesses interact and intervene between them in a tricky and a complicated manner. Notwithstanding the prevalence of this paradigm in biological and computer vision, we nevertheless propose to replace it with a new one, which we would like to designate as a two-part paradigm. In it, information contained in an image is initially extracted in an independent top-down manner by one part of the system, and then it is examined and interpreted by another, separate system part. We argue that the new paradigm seems to be more plausible than its forerunner. We provide evidence from human attention vision studies and insights of Kolmogorov's complexity theory to support these arguments. We also provide some reasons in favor of separate image interpretation issues

    Using Realistic Virtual Environments in the Study of Spatial Encoding

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    Computer generated virtual environments have reached a level of sophistication and ease of production that they are readily available for use in the average psychology laboratory. The potential benefits include cue control, incorporation of interactivity and novelty of environments used. The draw-backs include limitations in realism and lack of fidelity. In this chapter we describe our use of virtual environments to study how 3D space is encoded in humans with special emphasis on realism and interactivity. We describe the computational methods used to implement this realism and give examples from studies concerning spatial memory for object form, spatial layout and scene recognition
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