990 resultados para story image
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http://www.archive.org/details/bolengeastoryofg00dyeeuoft
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http://www.archive.org/details/anheroicbishopli00stocuoft
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http://www.archive.org/details/inojibwaycountry00scheiala
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http://www.archive.org/details/jubileechinamis00broouoft
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http://www.archive.org/details/johninnocent00canduoft
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http://www.archive.org/details/goodbirdindian00goodiala
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http://www.archive.org/details/daybreakinliving011984mbp
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http://books.google.com/books?vid=OCLC09108077
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http://www.archive.org/details/behindthegreatw00barnuoft/
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http://www.archive.org/details/arthurdouglasmi00douguoft
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http://www.archive.org/details/thestoryofthefuh00stocuoft
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Poster is based on the following paper: C. Kwan and M. Betke. Camera Canvas: Image editing software for people with disabilities. In Proceedings of the 14th International Conference on Human Computer Interaction (HCI International 2011), Orlando, Florida, July 2011.
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A method is proposed that can generate a ranked list of plausible three-dimensional hand configurations that best match an input image. Hand pose estimation is formulated as an image database indexing problem, where the closest matches for an input hand image are retrieved from a large database of synthetic hand images. In contrast to previous approaches, the system can function in the presence of clutter, thanks to two novel clutter-tolerant indexing methods. First, a computationally efficient approximation of the image-to-model chamfer distance is obtained by embedding binary edge images into a high-dimensional Euclide an space. Second, a general-purpose, probabilistic line matching method identifies those line segment correspondences between model and input images that are the least likely to have occurred by chance. The performance of this clutter-tolerant approach is demonstrated in quantitative experiments with hundreds of real hand images.
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We introduce "BU-MIA," a Medical Image Analysis system that integrates various advanced chest image analysis methods for detection, estimation, segmentation, and registration. BU-MIA evaluates repeated computed tomography (CT) scans of the same patient to facilitate identification and evaluation of pulmonary nodules for interval growth. It provides a user-friendly graphical user interface with a number of interaction tools for development, evaluation, and validation of chest image analysis methods. The structures that BU-MIA processes include the thorax, lungs, and trachea, pulmonary structures, such as lobes, fissures, nodules, and vessels, and bones, such as sternum, vertebrae, and ribs.