A Decision Fusion for Source Detection Based on Multimodal Supervised Spectral Unmixing
| Autor: | Franck Delayens, Anna Luiza Mendes Siqueira, Saïd Moussaoui, Laurent Grosset, Johan Lefeuvre |
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| Přispěvatelé: | Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ), TOTAL, Centre de recherche de Solaize (CReS) |
| Rok vydání: | 2021 |
| Předmět: |
Fusion
Signal processing Modality (human–computer interaction) business.industry Computer science Deep learning Pattern recognition Context (language use) signal separation multimodal supervided spectral unmixing Decomposition (computer science) Artificial intelligence Greedy algorithm Joint (audio engineering) business chemical mixture analysis [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing joint sparse recovery |
| Zdroj: | SSP 2021 IEEE Statistical Signal Processing Workshop (SSP) 2021 IEEE Statistical Signal Processing Workshop (SSP), Jul 2021, Rio de Janeiro, Brazil. pp.416-420, ⟨10.1109/SSP49050.2021.9513751⟩ |
| DOI: | 10.1109/ssp49050.2021.9513751 |
| Popis: | International audience; This paper addresses the problem of source detection in unknown chemical mixtures in the context of multimodal measurements of spectral data. The proposed approaches are based on supervised linear spectral unmixing under nonnegativity and sparsity constraints with adapted variants of the orthogonal matching pursuit algorithm. Two detection strategies are introduced: fusion of independent unimodal detection results and fusion by a joint multimodal decomposition and detection. Results are evaluated using a real database of ion mobility mass spectrometry (IMMS) data. A significant increase of the detection accuracy is obtained using the joint decomposition based decision as compared to the single modality detection results. |
| Databáze: | OpenAIRE |
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