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• W47378295 abstract "We present a novel method of Hierarchical Manifold Learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease." @default.
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• W47378295 date "2012-01-01" @default.
• W47378295 modified "2023-09-25" @default.
• W47378295 title "Hierarchical Manifold Learning" @default.
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• W47378295 doi "https://doi.org/10.1007/978-3-642-33415-3_63" @default.
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