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dc.contributor.advisorTomaso Poggioen_US
dc.contributor.authorTerashima, Yoshitoen_US
dc.contributor.otherCenter for Biological and Computational Learning (CBCL)en_US
dc.date.accessioned2009-05-11T17:30:10Z
dc.date.available2009-05-11T17:30:10Z
dc.date.issued2009-05-10
dc.identifier.urihttp://hdl.handle.net/1721.1/45516
dc.description.abstractWe present a biologically motivated method for scene image classification. The core of the method is to use shape based image property that is provided by a hierarchical feedforward model of the visual cortex [18]. Edge based and color based image properties are additionally used to improve the accuracy. The method consists of two stages of image analysis. In the first stage, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. In the second stage, a single classifier assigns the category of an image based on the probability distributions of the first stage classifier outputs. Experiments show that the method boosts the classification accuracy over the shape based model. We demonstrate that this method achieves a high accuracy comparable to other reported methods on publicly available color image dataset.en_US
dc.format.extent8 p.en_US
dc.relation.ispartofseriesCBCL-277
dc.relation.ispartofseriesMIT-CSAIL-TR-2009-020en_US
dc.subjectimage classificationen_US
dc.subjectvisionen_US
dc.titleScene Classification with a Biologically Inspired Methoden_US


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