FedSKD: Aggregation-Free Model-Heterogeneous Federated Learning via Multidimensional Similarity Knowledge Distillation for Medical Image Classification.
- DOI
- 10.1109/tnnls.2026.3684321
- Published
- 2026 Oct
- Container
- IEEE transactions on neural networks and learning systems
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- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3684321,
title = {FedSKD: Aggregation-Free Model-Heterogeneous Federated Learning via Multidimensional Similarity Knowledge Distillation for Medical Image Classification.},
author = {Weng Z and Cai W and Zhou B},
year = {2026},
journal = {IEEE transactions on neural networks and learning systems},
doi = {10.1109/tnnls.2026.3684321},
url = {https://doi.org/10.1109/tnnls.2026.3684321}
}RIS
TY - JOUR TI - FedSKD: Aggregation-Free Model-Heterogeneous Federated Learning via Multidimensional Similarity Knowledge Distillation for Medical Image Classification. AU - Weng Z AU - Cai W AU - Zhou B PY - 2026 JO - IEEE transactions on neural networks and learning systems DO - 10.1109/tnnls.2026.3684321 UR - https://doi.org/10.1109/tnnls.2026.3684321 ER -
APA
Z, W., W, C., & B, Z. (2026). FedSKD: Aggregation-Free Model-Heterogeneous Federated Learning via Multidimensional Similarity Knowledge Distillation for Medical Image Classification.. IEEE transactions on neural networks and learning systems. https://doi.org/10.1109/tnnls.2026.3684321
Source records
- pubmed · retrieved 2026-11-10T12:35:40.245Z