Publications

The following are publications by staff members of the Institute of Applied Mathematics and Physics (IAMP) arranged according to publication date:

Fischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Henrici, Andreas; Heitmann, Björn; Scarso, Alessandro; Caldarelli, Guido; Wilhelm, Dirk,

2024.

MuSe Net: a deep learning framework for trustworthy multiplet segmentation in 1D 1H NMR spectra [poster].

In:

Datalab-Symposium, Winterthur, Schweiz, 12. September 2024.

Winterthur:

ZHAW Zurich University of Applied Sciences.

Available from: https://doi.org/10.21256/zhaw-31444
Brunner, Stefan; Reif, Monika Ulrike; Senn, Christoph,

2024.

Deep Ensemble Novelty Detection : novelty detection and fault identification in multivariate data [paper].

In:

Yang, XS.; Sherratt, S.; Dey, N.; Joshi, A., eds.,

Proceedings of Ninth International Congress on Information and Communication Technology.

9th International Congress on Information and Communication Technology (ICICT), London, United Kindom, 19-22 February 2024.

Singapore:

Springer.

pp. 443-461.

Lecture Notes in Networks and Systems ; 1003.

Available from: https://doi.org/10.1007/978-981-97-3302-6_36
Schmid, Nicolas; Wanner, Marc; Fischetti, Giulia; Meshkian, Mohsen; Bruderer, Simon; Henrici, Andreas; Wegner, Jan Dirk; Sigel, Roland K. O.; Heitmann, Bjoern; Wilhelm, Dirk,

2024.

Automated spin system analysis in NMR spectroscopy with SpinDETR : a deep learning approach [poster].

In:

20th European Magnetic Resonance Congress (EUROMAR), Bilbao, Spain, 30 June - 4 July 2024.

ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

Available from: https://doi.org/10.21256/zhaw-31101
Fischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Henrici, Andreas; Heitmann, Bjoern; Scarso, Alessandro; Caldarelli, Guido; Wilhelm, Dirk,

2024.

MuSe Net : a deep learning framework for trustworthy multiplet segmentation in 1D 1H NMR spectra [poster].

In:

20th European Magnetic Resonance Congress (EUROMAR), Bilbao, Spain, 30 June - 4 July 2024.

ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

Available from: https://doi.org/10.21256/zhaw-31102
Venturini, Francesca; Fluri, Silvan; Mejari, Manas; Baumgartner, Michael; Piga, Dario; Michelucci, Umberto,

2024.

Machine learning-enhanced fluorescence spectroscopy for the quality assessment of extra virgin olive oil during ageing [paper].

In:

Berghmans, Francis; Zergioti, Ioanna, eds.,

Optical Sensing and Detection VIII.

SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024.

SPIE.

pp. 129991F.

Proceedings of SPIE ; 12999.

Available from: https://doi.org/10.1117/12.3016879