Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-27429Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Schmid, Nicolas | - |
| dc.contributor.author | Bruderer, Simon | - |
| dc.contributor.author | Fischetti, Giulia | - |
| dc.contributor.author | Paruzzo, Federico | - |
| dc.contributor.author | Toscano, Giuseppe | - |
| dc.contributor.author | Graf, Dominik | - |
| dc.contributor.author | Fey, Michael | - |
| dc.contributor.author | Ziebart, Volker | - |
| dc.contributor.author | Henrici, Andreas | - |
| dc.contributor.author | Grabner, Helmut | - |
| dc.contributor.author | Wegner, Jan Dirk | - |
| dc.contributor.author | Sigel, Roland K.O. | - |
| dc.contributor.author | Heitmann, Björn | - |
| dc.contributor.author | Wilhelm, Dirk | - |
| dc.date.accessioned | 2023-03-20T16:25:52Z | - |
| dc.date.available | 2023-03-20T16:25:52Z | - |
| dc.date.issued | 2023-01-11 | - |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/27429 | - |
| dc.language.iso | en | de_CH |
| dc.publisher | ZHAW Zürcher Hochschule für Angewandte Wissenschaften | de_CH |
| dc.rights | Licence according to publishing contract | de_CH |
| dc.subject.ddc | 006: Spezielle Computerverfahren | de_CH |
| dc.subject.ddc | 530: Physik | de_CH |
| dc.title | Deconvolution of NMR spectra : a deep learning-based approach | de_CH |
| dc.type | Konferenz: Poster | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | School of Engineering | de_CH |
| zhaw.organisationalunit | Institut für Angewandte Mathematik und Physik (IAMP) | de_CH |
| zhaw.organisationalunit | Institut für Datenanalyse und Prozessdesign (IDP) | de_CH |
| dc.identifier.doi | 10.21256/zhaw-27429 | - |
| zhaw.conference.details | Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023 | de_CH |
| zhaw.funding.eu | No | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.publication.status | publishedVersion | de_CH |
| zhaw.publication.review | Peer review (Abstract) | de_CH |
| zhaw.webfeed | Datalab | de_CH |
| zhaw.webfeed | ZHAW digital | de_CH |
| zhaw.funding.zhaw | Maschinelles Lernen für NMR-Spektroskopie | de_CH |
| zhaw.author.additional | No | de_CH |
| zhaw.display.portrait | Yes | de_CH |
| Appears in collections: | Publikationen School of Engineering | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_Schmid-etal_Deconvolution-of-NMR-spectra_Datalab-Symposium-Poster.pdf | 3.03 MB | Adobe PDF |  View/Open |
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Schmid, N., Bruderer, S., Fischetti, G., Paruzzo, F., Toscano, G., Graf, D., Fey, M., Ziebart, V., Henrici, A., Grabner, H., Wegner, J. D., Sigel, R. K. O., Heitmann, B., & Wilhelm, D. (2023, January 11). Deconvolution of NMR spectra : a deep learning-based approach. Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. https://doi.org/10.21256/zhaw-27429
Schmid, N. et al. (2023) ‘Deconvolution of NMR spectra : a deep learning-based approach’, in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-27429.
N. Schmid et al., “Deconvolution of NMR spectra : a deep learning-based approach,” in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023, Jan. 2023. doi: 10.21256/zhaw-27429.
SCHMID, Nicolas, Simon BRUDERER, Giulia FISCHETTI, Federico PARUZZO, Giuseppe TOSCANO, Dominik GRAF, Michael FEY, Volker ZIEBART, Andreas HENRICI, Helmut GRABNER, Jan Dirk WEGNER, Roland K.O. SIGEL, Björn HEITMANN und Dirk WILHELM, 2023. Deconvolution of NMR spectra : a deep learning-based approach. In: Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. Conference poster. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. 11 Januar 2023
Schmid, Nicolas, Simon Bruderer, Giulia Fischetti, Federico Paruzzo, Giuseppe Toscano, Dominik Graf, Michael Fey, et al. 2023. “Deconvolution of NMR Spectra : A Deep Learning-Based Approach.” Conference poster. In Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-27429.
Schmid, Nicolas, et al. “Deconvolution of NMR Spectra : A Deep Learning-Based Approach.” Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2023, https://doi.org/10.21256/zhaw-27429.
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