Abstract: Generative Adversarial Networks (GANs) significantly advanced image generation but their performance heavily depends on abundant training data. In scenarios with limited data, GANs often ...
Do you agree? Data normalization isn’t the finish line. Harmonization is. Even after basic normalization, datasets can drift across plates, batches, cohorts, and time — blurring ...
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