Bettina Finzel
Zitiert von
Zitiert von
The Next Generation of Medical Decision Support: A Roadmap Toward Transparent Expert Companions
S Bruckert, B Finzel, U Schmid
Frontiers in Artificial Intelligence 3, 75, 2020
Mutual Explanations for Cooperative Decision Making in Medicine
U Schmid, B Finzel
KI-Künstliche Intelligenz, 227-233, 2020
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts
G Schwalbe, B Finzel, submitted to Data Mining and Knowledge Discovery, 2021
From beliefs to intention: mentoring as an approach to motivate female high school students to enrol in computer science studies
B Finzel, H Deininger, U Schmid
Proceedings of the 4th Conference on Gender & IT, 251-260, 2018
Towards understanding mobility in museums
G Elmamooz, B Finzel, D Nicklas
Datenbanksysteme für Business, Technologie und Web (BTW 2017)-Workshopband, 2017
Explanation as a Process: User-Centric Construction of Multi-level and Multi-modal Explanations
B Finzel, DE Tafler, S Scheele, U Schmid
German Conference on Artificial Intelligence (Künstliche Intelligenz), 80-94, 2021
Verifying Deep Learning-based Decisions for Facial Expression Recognition
I Rieger, R Kollmann, B Finzel, D Seuss, U Schmid
28th European Symposium on Artificial Neural Networks, Computational …, 2020
Uncovering the Bias in Facial Expressions
J Deuschel, B Finzel, I Rieger
arXiv preprint arXiv:2011.11311, 2020
A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts
G Schwalbe, B Finzel
Data Mining and Knowledge Discovery, 1-59, 2023
Multimodal Explanations for User-centric Medical Decision Support Systems.
B Finzel, DE Tafler, AM Thaler, U Schmid
HUMAN@ AAAI Fall Symposium, 2021
Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs
B Finzel, A Saranti, A Angerschmid, D Tafler, B Pfeifer, A Holzinger
KI-Künstliche Intelligenz 36 (3), 271-285, 2022
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition
I Rieger, J Pahl, B Finzel, U Schmid
2022 26th International Conference on Pattern Recognition (ICPR), 798-804, 2022
Deriving Temporal Prototypes from Saliency Map Clusters for the Analysis of Deep-Learning-based Facial Action Unit Classification
B Finzel, R Kollmann, I Rieger, J Pahl, U Schmid
Make Pain Estimation Transparent: A Roadmap to Fuse Bayesian Deep Learning and Inductive Logic Programming
I Rieger, B Finzel, D Seuß, T Wittenberg, U Schmid
41st Annual International Conference of the IEEE Engineering in Medicine …, 2019
Explaining and Evaluating Deep Tissue Classification by Visualizing Activations of Most Relevant Intermediate Layers
A Mohammed, C Geppert, A Hartmann, P Kuritcyn, V Bruns, U Schmid, ...
Current Directions in Biomedical Engineering 8 (2), 229-232, 2022
Regularization by Integrating Co-Occurrence Domain Knowledge for Affect Recognition
I Rieger, J Pahl, B Finzel, U Schmid
Uni. vers Forschung: das Magazin der Otto-Friedrich-Universität Bamberg
P Achter, R Braches-Chyrek, M Düchs, T Färber, B Finzel, F Ganesch, ...
Otto-Friedrich-Universität, 2021
Korrigierbares maschinelles Lernen mithilfe wechselseitiger Erklärungen am Beispiel der Medizin
B Finzel
Vol. 44, Medizininformatik, 2020
Explaining Relational Concepts: When Visualisation and Visual Interpretation of a Deep Neural Network's Decision are not enough
B Finzel, J Rabold, U Schmid
Europäische Konferenz zur Datenanalyse (ECDA, 18.-20. März 2019, Bayreuth …, 2019
Erklärbare KI für medizinische Anwendungen
B Finzel, U Schmid
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