Cross-Modal Information Recovery and Enhancement Using Multiple-Input-Multiple-Output Variational Autoencoder

Motivated by the cross-modal information processing mechanism of human brain, vertebrates, and invertebrates, we propose a multiple-input-multiple-output (MIMO) variational autoencoder (VAE) and subsequently apply it to cross-modal information recovery and enhancement. For a cross-modal system with...

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Bibliographic Details
Published in:	IEEE internet of things journal Vol. 11; no. 15; pp. 26470 - 26480
Main Author:	Liang, Jessica E.
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Audio data Autoencoders Brain Coders Complexity Cross-modal information processing Data integration Data processing Decoders Decoding Image reconstruction Information theory Internet of Things Linearization Machine learning MIMO multiple-input–multiple-output (MIMO) Recovery Robot sensing systems Robots variational autoencoder (VAE) Vertebrates Visualization
ISSN:	2327-4662, 2327-4662
Online Access:	Get full text
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