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- W4386323810 abstract "Most odour recognition algorithms rely only on data from chemical (gas) sensors. There are scenarios in which it would help to include other modalities (data from other types of sensors) in the recognition. In this paper we describe a process of combining gas sensor data and image data for binary classification. For that, a synthetic dataset was assembled, and different neural networks were trained. We found that combining the modalities makes the classification perform better and be more stable. The next step is the collection of multimodal data and validating this multimodal approach on a non-synthetic dataset." @default.
- W4386323810 created "2023-09-01" @default.
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- W4386323810 date "2023-06-19" @default.
- W4386323810 modified "2023-09-27" @default.
- W4386323810 title "Work-in-Progress: Multimodal Odour and Image Recognition on Synthetic Dataset" @default.
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- W4386323810 doi "https://doi.org/10.1109/isie51358.2023.10228134" @default.
- W4386323810 hasPublicationYear "2023" @default.
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