CORDIS Project
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This project develops advanced sparse models to enhance data processing efficiency for high-dimensional digital data. By leveraging compressed sensing and random projections, it aims to improve data acquisition and analysis in fields like audiovisual and biomedical applications.
Sparse models are at the core of many research domains where the large amount and high-dimensionality of digital data requires concise data descriptions for efficient information processing. A flagship application of sparsity is compressed sensing, which exploits sparsity for data acquisition using limited resources.
Besides sparsity, a key pillar of compressed sensing is the use of random low-dimensional projections.The standard principle of general sparse and redundant representations is to re…
INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
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