Showing results 23 to 42 of 131
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Issue Date | Title | Involved Person(s) |
11-Jan-2023 | certAInty : a certification scheme for AI systems (Innosuisse project) | Weng, Joanna; Reif, Monika; Chavarriaga, Ricardo; Schilling, Frank-Peter |
May-2022 | Chemical analysis of olive oils from fluorescence spectra thanks to one-dimensional convolutional neural networks | Sperti, Michela; Gucciardi, Arnaud; Michelucci, Umberto; Venturini, Francesca; Deriu, Marco Agostino . |
1-Dec-2020 | Combined multilateration with machine learning for enhanced aircraft localization | Figuet, Benoit; Monstein, Raphael; Felux, Michael |
6-Apr-2022 | Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil | Gucciardi, Arnaud; Michelucci, Umberto; Venturini, Francesca; Sperti, Michela; Martos, Vanessa M., et al |
May-2022 | Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil | Arnaud, Gucciardi; Michelucci, Umberto; Venturini, Francesca; Sperti, Michela; Martos, Vanessa M., et al |
Jan-2020 | Comparison of statistical learning approaches for cerebral aneurysm rupture assessment | Detmer, Felicitas J.; Lückehe, Daniel; Mut, Fernando; Slawski, Martin; Hirsch, Sven, et al |
21-Jun-2022 | Convolutional neural nets with hyperparameter optimization and feature importance for power system static security assessment | Ramirez Gonzalez, Miguel; Segundo Sevilla, Felix Rafael; Korba, Petr; Castellanos-Bustamante, Rafael |
2016 | Data Scientist als Beruf | Stockinger, Kurt; Stadelmann, Thilo; Ruckstuhl, Andreas |
2019 | Data warehousing and exploratory analysis for market monitoring | Geiger, Melanie; Stockinger, Kurt |
Feb-2023 | Deconvolution of 1D NMR spectra : a deep learning-based approach | Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G., et al |
13-Jul-2022 | Deconvolution of NMR spectra : a deep learning-based approach | Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe, et al |
2023 | Deep ensemble inverse model for image-based estimation of solar cell parameters | Battaglia, Mattia; Comi, Ennio; Stadelmann, Thilo; Hiestand, Roman; Ruhstaller, Beat, et al |
22-Jun-2023 | Deep learning for predictive maintenance : scalable implementation in operational setups | Goren Huber, Lilach |
2023 | Deep learning for robust and explainable models in computer vision | Schwenker, Friedhelm; Stadelmann, Thilo; Jaggi, Martin; Amirian, Mohammadreza |
2020 | Deep learning for understanding satellite imagery : an experimental survey | Mohanty, Sharada Prasanna; Czakon, Jakub; Kaczmarek, Kamil A.; Pyskir, Andrzej; Tarasiewicz, Piotr, et al |
Mar-2023 | Deep learning super resolution for high-speed excitation emission matrix measurements | Michelucci, Umberto; Fluri, Silvan; Baumgartner, Michael; Venturini, Francesca |
2022 | Deep partial hedging | Hou, Songyan; Krabichler, Thomas; Wunsch, Marcus |
2020 | Deep-learning for multi-parameter luminescence sensing : demonstration of dual sensor | Venturini, Francesca; Michelucci, Umberto; Baumgartner, Michael |
Mar-2021 | Dependable neural networks through redundancy, a comparison of redundant architectures | Doran, Hans Dermot; Ganz, David; Ielpo, Gianluca; Zapke, Michael |
Mar-2024 | Detecting anomalies in time series using kernel density approaches | Frehner, Robin; Wu, Kesheng; Sim, Alexander; Kim, Jinoh; Stockinger, Kurt |