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About Multimodal Data Fusion Anoverview of Methods
This paper provides an overview of multimodal data fusion, which involves analyzing multiple datasets that provide information about the same phenomenon. The paper discusses why multimodal data fusion is useful, providing a more complete understanding than single datasets alone. It also covers several data-driven methods for performing multimodal data fusion, such as matrix and tensor decompositions, that account for diversity across datasets. The goal is to introduce readers to the broad field of multimodal data fusion and its opportunities across many application domains.
Detailed Information
| Author: | ['Samuele Tesfaye'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 29 |
| Language: | English |
| Format: | |
| Price: | FREE |
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