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    BMCBI
    2006
    148views more  BMCBI 2006»
    Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores
    14 years 9 months ago
    Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores
    Download  www.biomedcentral.com
    Background: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epi...
    Jesper Salomon, Darren R. Flower
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    CVPR
    2005
    IEEE
    229views Computer Vision» more  CVPR 2005»
    Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors
    15 years 11 months ago
    Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors
    Download  www.cvc.uab.es
    We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
    Jaume Amores, Nicu Sebe, Petia Radeva
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    CLOR
    2006
    282views Computer Vision» more  CLOR 2006»
    An Implicit Shape Model for Combined Object Categorization and Segmentation
    14 years 11 months ago
    An Implicit Shape Model for Combined Object Categorization and Segmentation
    Download  ftp.vision.ee.ethz.ch
    We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior...
    Bastian Leibe, Ales Leonardis, Bernt Schiele
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    PAMI
    2008
    250views more  PAMI 2008»
    Combined Top-Down/Bottom-Up Segmentation
    14 years 9 months ago
    Combined Top-Down/Bottom-Up Segmentation
    Download  cbcl.mit.edu
    We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
    Eran Borenstein, Shimon Ullman
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    ICCV
    2007
    IEEE
    236views Computer Vision» more  ICCV 2007»
    Active Learning with Gaussian Processes for Object Categorization
    15 years 11 months ago
    Active Learning with Gaussian Processes for Object Categorization
    Download  people.csail.mit.edu
    Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
    Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
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