RetinaDA unites six public fundus sets into a 512 × 512 macula-centered benchmark with built-in domain gaps, enabling ...
The Data Provenance Explorer can help machine-learning practitioners make more informed choices about the data they train their models on, which could improve the accuracy of models deployed in the ...
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