2 papers
q-bio.QM2026
Batch effects can impair federated learning in multi-center omics studies
Yuliya Burankova, Julian Klemm, Jens J. G. Lohmann +5
Federated learning (FL) enables collaborative analysis of biomedical data without exchanging sensitive patient-level information, but its performance in multi-center studies may be…
cs.LG2025
FTA-FTL: A Fine-Tuned Aggregation Federated Transfer Learning Scheme for Lithology Microscopic Image Classification
Keyvan RahimiZadeh, Ahmad Taheri, Jan Baumbach +5
Lithology discrimination is a crucial activity in characterizing oil reservoirs, and processing lithology microscopic images is an essential technique for investigating fossils and…