Transport Model for Feature Extraction
نویسندگان
چکیده
We present a new feature extraction method for noisy datasets with intricate spatio-temporal structures that is based on the concept of transport operators graphs. The proposed approach generalizes and extends many existing data representation methodologies built upon diffusion processes to domain where dynamical systems play key role. main advantage this comes from ability exploit different relationships than those arising in context of, e.g., graph Laplacians. Fundamental properties are proved. demonstrate flexibility by introducing several diverse examples transformations. close paper series computational experiments applications problem image clustering classification hyperspectral data, illustrate practical implications our algorithm its quantify aspects within complicated datasets.
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ژورنال
عنوان ژورنال: SIAM journal on mathematics of data science
سال: 2021
ISSN: ['2577-0187']
DOI: https://doi.org/10.1137/19m1296926