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111 |
A framework for explainable root cause analysis in manufacturing systems – combining machine learning, explainable artificial intelligence and the Ishikawa model for industrial manufacturing
Kiefer, Daniel. - Reutlingen : Hochschule Reutlingen, 2025
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112 |
A framework for sensor fault detection and management in low-power IoT edge devices
Attarha, Shadi. - Bremen : Staats- und Universitätsbibliothek Bremen, 2025
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113 |
A framework to evaluate machine learning crystal stability predictions
Riebesell, Janosh. - Berlin : Bundesanstalt für Materialforschung und -prüfung (BAM), 2025
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114 |
A Kanban-based Approach to Manage Machine Learning Projects in Manufacturing
Schreier, Ulf. - Furtwangen : Hochschule Furtwangen, 2025
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115 |
A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery
Semnani, Parastoo. - Berlin : Technische Universität Berlin, 2025
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116 |
A machine learning-based framework and open-source software for non intrusive water monitoring
Gross, Marie-Philine. - Berlin : Technische Universität Berlin, 2025
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117 |
A machine learning based regulatory risk index for cryptocurrencies
Ni, Xinwen. - Berlin : Humboldt-Universität zu Berlin, 2025
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118 |
A new design method to account for interlaminar stresses in laminated composites using machine learning
Gadinger, Marc. - Hamburg : Technische Universität Hamburg. Universitätsbibliothek, 2025
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119 |
A novel framework for uncertainty qantification via proper scores for classification and beyond
Gruber, Sebastian G.. - Frankfurt am Main : Universitätsbibliothek Johann Christian Senckenberg, 2025
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120 |
A novel machine-learning approach to unlock technical lignin classification by NIR spectroscopy - bench to handheld
Fink, Friedrich. - Berlin : Bundesanstalt für Materialforschung und -prüfung (BAM), 2025
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