86 research outputs found

    Superpixel Graph Label Transfer with Learned Distance Metric

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    We present a fast approximate nearest neighbor algorithm for semantic segmentation. Our algorithm builds a graph over superpixels from an annotated set of training images. Edges in the graph represent approximate nearest neighbors in feature space. At test time we match superpixels from a novel image to the training images by adding the novel image to the graph. A move-making search algorithm allows us to leverage the graph and image structure for finding matches. We then transfer labels from the training images to the image under test. To promote good matches between superpixels we propose to learn a distance metric that weights the edges in our graph. Our approach is evaluated on four standard semantic segmentation datasets and achieves results comparable with the state-of-the-art

    Abstracts of presentations on plant protection issues at the xth international congress of virology: August 11-16,1996 Binyanei haOoma, Jerusalem, Israel Part 2 Plenary Lectures

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    Abstracts of presentations on plant protection issues at the xth international congress of virology: August 11-16, 1996 Binyanei haOoma, Jerusalem Iarael part 3(final part)

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    Correction

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    A study of oxygen ion conductivity in the system Nd(2)Zr(2)0(7)-Nd(2)Ce(2)0(7) and related materials

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    The Detection of Structural Defects in GaAs by Electrochemical Etching

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