Soferi_mix -

SoftMix operates on the principle of from different images to create a composite training sample. Unlike traditional "Mixup" (which blends images pixel-wise) or "CutMix" (which replaces a hard rectangular patch), SoftMix utilizes a "softer" approach to blending boundaries. Selection : Two images from the training set are selected. Patching : The images are divided into discrete patches.

: Instead of hard-swapping patches, SoftMix applies a transition mask that blends the features of both source images at the edges of the patch. soferi_mix

SoftMix: A Novel Data Augmentation for Patched Medical Image Classification AI Demystified: Medical Imaging Accuracy Systematic Review of Data-Centric AI SoftMix operates on the principle of from different