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About Multimodal Deep Learning
The paper surveys recent advances in multimodal machine learning and presents a new taxonomy. It identifies five core technical challenges in multimodal machine learning: representation, translation, alignment, fusion, and co-learning. These challenges stem from the heterogeneity of multimodal data and the need to relate information across modalities. The taxonomy goes beyond early and late fusion to characterize challenges that require tackling representation, mapping between modalities, identifying relations between modal elements, combining information, and transferring knowledge across modalities.
Detailed Information
| Author: | ['sagnik ghosal'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 21 |
| Language: | English |
| Format: | |
| Price: | FREE |
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