| 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
2/164129http://resolver.sub.uni-goettingen.de/purl?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)