Name
Title | ||
|---|---|---|
Relations Between Explainability, Evaluation and Trust in AI-Based Information Fusion Systems |
Abstract | ||
|---|---|---|
Explainability is generally considered an important means to gain trust in complex automated decision support systems. Different types of explainability of processes and models used in a complex information fusion solution based on Artificial Intelligence (AI) are relevant throughout its life-cycle, i.e. during the system development as well as its deployment. However, it is often difficult to und... |
Year | Venue | Keywords |
|---|---|---|
2021 | 2021 IEEE 24th International Conference on Information Fusion (FUSION) | Decision support systems,Adaptation models,Runtime,Automation,Conferences,Buildings,Human factors |
DocType | ISBN | Citations |
Conference | 978-1-7377497-1-4 | 1 |
PageRank | References | Authors |
0.37 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| G. Pavlin | 1 | 1 | 0.71 |
| J. P. de Villiers | 2 | 1 | 0.71 |
| J. Ziegler | 3 | 1 | 0.71 |
| A.-L. Jousselme | 4 | 1 | 0.37 |
| P. Costa | 5 | 1 | 0.37 |
| K. Laskey | 6 | 1 | 0.71 |
| A. de Waal | 7 | 1 | 1.05 |
| Erik Blasch | 8 | 1051 | 90.91 |
| L. Jansen | 9 | 1 | 0.37 |