Magnification Generalization For Histopathology Image Embedding

@article{Sikaroudi2021MagnificationGF,
  title={Magnification Generalization For Histopathology Image Embedding},
  author={Milad Sikaroudi and Benyamin Ghojogh and Fakhri Karray and Mark Crowley and Hamid R. Tizhoosh},
  journal={2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
  year={2021},
  pages={1864-1868}
}
Histopathology image embedding is an active research area in computer vision. Most of the embedding models exclusively concentrate on a specific magnification level. However, a useful task in histopathology embedding is to train an embedding space regardless of the magnification level. Two main approaches for tackling this goal are domain adaptation and domain generalization, where the target magnification levels may or may not be introduced to the model in training, respectively. Although… 
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