Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1432-119X

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning ; day:8 ; month:11 ; year:2021 ; pages:1-11
Histochemistry and cell biology ; (8.11.2021), 1-11

Creator: Ritschar, Sven
Schirmer, Elisabeth
Hufnagl, Benedikt
Löder, Martin G. J.
Römpp, Andreas
Laforsch, Christian

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00418-021-02037-1

URN: urn:nbn:de:101:1-2022012120593960873428

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:27 AM CEST

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Ritschar, Sven
Schirmer, Elisabeth
Hufnagl, Benedikt
Löder, Martin G. J.
Römpp, Andreas
Laforsch, Christian
SpringerLink (Online service)

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Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

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Other Objects (12)

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

Analysis of data from multimodal chemical characterizations of plant tissues

Within-class multimodal classification

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DAMA: A Dynamic Classification of Multimodal Ambiguities

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Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

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