Jan 27, 2022 · In this paper, we take a data-centric approach to the transfer learning problem and examine the existence of generalizable knowledge between ...
Us- ing cross transfer over nine classification task datasets, we evaluate both the quantity and quality of transferable information between datasets; iii) we ...
Jan 27, 2022 · In this paper, we take a data-centric approach to the transfer learning problem and examine the existence of generalizable knowledge between ...
Overview. In computational pathology, the lack of well-annotated datasets obstructs the application of deep learning techniques. Since pathologist time is ...
Nov 15, 2024 · Different techniques are available in the specialized literature in order to investigate patterns in histological images, such as for the CR ...
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HistoKT: Cross Knowledge Transfer in Computational Pathology ... In this paper, we take a data-centric approach to the transfer learning problem and examine the ...
In this paper, we take a data-centric approach to the transfer learning problem and examine the existence of generalizable knowledge between histopathological ...
Journal of Pathology Informatics, 100357, 2024. 35, 2024. Histokt: Cross knowledge transfer in computational pathology. R Zhang, J Zhu, S Yang, MS Hosseini, A ...
Dec 12, 2024 · Histokt: Cross Knowledge Transfer in Computational Pathology. ICASSP ... HistoKT: Cross Knowledge Transfer in Computational Pathology.
Jan 23, 2024 · HistoKT: Cross Knowledge Transfer in Computational Pathology. Authors: R Zhang, J Zhu, S Yang, MS Hosseini, A Genovese, L Chen, C Rowsell, et ...