| Property | Value |
| Working Groups | RG Bonn |
| Subproject | Z2 |
| Open Access | Yes |
| Publication Type | Journal Article |
| Peer Reviewed | Yes |
| DOI | 10.1016/j.array.2026.100725 |
| Publication Year | 2026 |
| Title | On the power and limits of foundation model image embeddings for privacy-preserving federated learning |
| Journal | Array |
| ISSN | 2590-0056 |
| eISSN | 2590-0056 |
| URL | https://doi.org/10.1016/j.array.2026.100725 |
| Pages | 100725 |
| Journal Abbreviation | Array |
| Authors | Lohmann J, Witte A, Maier A, Saak CC, Sauter G, Zimmermann M, Bonn S, Baumbach J |
| First Author | Lohmann J |
| Last Author | Baumbach J |
External Resources
gro-2/164129http://resolver.sub.uni-goettingen.de/purl?gro-2/164129
GRO.publications identifier
00g30e956https://ror.org/00g30e956
ROR identifier (00g30e956, Universität Hamburg)
01zgy1s35https://ror.org/01zgy1s35
ROR identifier (01zgy1s35, University Medical Center Hamburg-Eppendorf)
03yrrjy16https://ror.org/03yrrjy16
ROR identifier (03yrrjy16, University of Southern Denmark)