| CPC G06T 7/11 (2017.01) [G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06T 7/0012 (2013.01); G06T 19/00 (2013.01); G06V 10/25 (2022.01); G06T 2207/30068 (2013.01); G06T 2219/004 (2013.01)] | 20 Claims |

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1. A method, comprising:
identifying, by a computing system, for a first tile of a biomedical image, a first patch generated from the first tile at a first magnification factor and a second patch generated from the first tile at a second magnification factor, the first tile including at least a portion of a region of interest (ROI) in the biomedical image;
applying, by the computing system, the first patch and the second patch to a machine learning (ML) model, the ML model comprising:
a first network to generate a first plurality of feature maps using the first patch,
a second network to generate a second feature map using (i) the second patch and (ii) the first plurality of feature maps transferred from the first network in accordance with a shift between the first network and the second network, and
a terminal block to generate a second tile using the second feature map, the second tile identifying the portion of the ROI in the first tile; and
storing, by the computing system, in one or more data structures, an association between the biomedical image and the second tile.
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