Predicting the crossmodal correspondences of odors using an electronic nose

Predicting the crossmodal correspondences of odors using an electronic nose

When designing multisensorial experiences, robustly predicting the crossmodal perception of olfactory stimuli is a critical factor. We investigate the possibility of predicting olfactory crossmodal correspondences using the underlying physicochemical features. An electronic nose was tuned to the cro...

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Bibliographic Details
Main Authors: Ryan J. Ward, Shammi Rahman, Sophie Wuerger, Alan Marshall
Format: Article
Language:English
Published: Elsevier 2022-04-01
Series:Heliyon
Subjects:
Crossmodal correspondences
Crossmodal associations
Machine learning
Electronic nose
Regression
Odors
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844022005722

Internet

http://www.sciencedirect.com/science/article/pii/S2405844022005722

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