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- W2076003885 abstract "This work deals with the design of a classification method for cells extracted from Indirect Immunofluorescence images. In particular, we propose to use a dense local descriptor invariant both to scale changes and to rotations in order to classify the six categories of staining patterns of the cells. The descriptor is able to give a compact and discriminative representation and combines a log-polar sampling with spatially-varying gaussian smoothing applied on the gradients images in specific directions. Bag of Words is finally used to perform classification and experimental results show very good performance." @default.
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- W2076003885 date "2014-08-24" @default.
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- W2076003885 title "Biologically-Inspired Dense Local Descriptor for Indirect Immunofluorescence Image Classification" @default.
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- W2076003885 doi "https://doi.org/10.1109/i3a.workshop.2014.18" @default.
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