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Showing results 1 to 20 of 81  next >
Issue DateTitleInvolved Person(s)
14-Jul-2022A deep ensemble learning method for automatic classification of multiplets in 1D NMR spectraFischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Paruzzo, Federico; Toscano, Giuseppe, et al
26-Jan-2024A generic machine learning framework for fully-unsupervised anomaly detection with contaminated dataUlmer, Markus; Zgraggen, Jannik; Goren Huber, Lilach
2-Sep-2020A hybrid deep learning approach for forecasting air temperatureGygax, Gregory; Schüle, Martin
Jul-2020A methodology for creating question answering corpora using inverse data annotationDeriu, Jan Milan; Mlynchyk, Katsiaryna; Schläpfer, Philippe; Rodrigo, Alvaro; von Grünigen, Dirk, et al
9-Jun-2021A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applicationsSimmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter, et al
15-Oct-2019Advanced applied deep learning : convolutional neural networks and object detectionMichelucci, Umberto
Jan-2024Artifact reduction in 3D and 4D cone-beam computed tomography images with deep learning - a reviewAmirian, Mohammadreza; Barco, Daniel; Herzig, Ivo; Schilling, Frank-Peter
2021Artificial neural networks to impute rounded zeros in compositional dataTempl, Matthias
18-Dec-2020Artificial neural networks to impute rounded zeros in compositional dataTempl, Matthias
21-Dec-2023Assessing deep learning : a work program for the humanities in the age of artificial intelligenceSegessenmann, Jan; Stadelmann, Thilo; Davison, Andrew; Dürr, Oliver
28-Aug-2023Assessing deep learning : a work program for the humanities in the age of artificial intelligenceSegessenman, Jan; Stadelmann, Thilo; Andrew, Davison; Oliver, Dürr
11-Jan-2023Automatic classification of signal regions in 1H nuclear magnetic resonance spectraFischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Caldarelli, Guido; Scarso, Alessandro, et al
2022Automatic interpretation of NMR spectra using neural networksSchüle, Martin; Bruderer, Simon; Graf, Dominik
2019Automatisierte Erkennung der Balzaktivität von Birkhähnen (Tetrao tetrix) in R anhand bioakustischer AufnahmenSuter, Stefan; Stephani, Annette; Burkhalter, Felix
14-Jun-2019Beyond ImageNet : deep learning in industrial practiceStadelmann, Thilo; Tolkachev, Vasily; Sick, Beate; Stampfli, Jan; Dürr, Oliver
2021Can we ignore the compositional nature of compositional data by using deep learning aproaches?Templ, Matthias
2020Constructing a reliable health indicator for bearings using convolutional autoencoder and continuous wavelet transformKaji, Mohammadreza; Parvizian, Jamshid; van de Venn, Hans Wernher
4-Aug-2021Convolutional neural network based approach for static security assessment of power systemsRamirez Gonzalez, Miguel; Segundo Sevilla, Felix Rafael; Korba, Petr
Feb-2023Deconvolution of 1D NMR spectra : a deep learning-based approachSchmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G., et al
13-Jul-2022Deconvolution of NMR spectra : a deep learning-based approachSchmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe, et al
Showing results 1 to 20 of 81  next >