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- W2069426705 abstract "This work considers the problem of combining high dimensional data acquired from multiple sensors for the purpose of detection and classification. The sampled data are viewed as a geometric object living in a highdimensional space. Through an appropriate, distance preserving projection, those data are reduced to a lowdimensional space. In this reduced space it is shown that different physics of the sampled phenomena reside on different portions of the resulting manifold allowing for classification. Moreover, we show that data acquired from multiple sources collected from the same underlying physical phenomenon can be readily combined in the low-dimensional space i.e. fused. The process is demonstrated on maritime imagery collected from a visible-band camera." @default.
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- W2069426705 date "2011-05-13" @default.
- W2069426705 modified "2023-09-23" @default.
- W2069426705 title "On the use of diffusion maps for image fusion" @default.
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- W2069426705 doi "https://doi.org/10.1117/12.884266" @default.
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