Deconvolution of NMR spectra : a deep learning-based approach

Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Ziebart, Volker; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K.O.; Heitmann, Björn; Wilhelm, Dirk

doi:10.21256/zhaw-27429

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-27429

Publication type:	Conference poster
Type of review:	Peer review (abstract)
Title:	Deconvolution of NMR spectra : a deep learning-based approach
Authors:	Schmid, Nicolas Bruderer, Simon Fischetti, Giulia Paruzzo, Federico Toscano, Giuseppe Graf, Dominik Fey, Michael Ziebart, Volker Henrici, Andreas Grabner, Helmut Wegner, Jan Dirk Sigel, Roland K.O. Heitmann, Björn Wilhelm, Dirk
et. al:	No
DOI:	10.21256/zhaw-27429
Conference details:	Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023
Issue Date:	11-Jan-2023
Publisher / Ed. Institution:	ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Language:	English
Subject (DDC):	006: Special computer methods 530: Physics
URI:	https://digitalcollection.zhaw.ch/handle/11475/27429
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Applied Mathematics and Physics (IAMP) Institute of Data Analysis and Process Design (IDP)
Published as part of the ZHAW project:	Maschinelles Lernen für NMR-Spektroskopie
Appears in collections:	Publikationen School of Engineering

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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.