A multitask learning method with instance-aware pseudo-labeling and class-focused contrastive learning outperforms prior UDA and WDA techniques for weakly supervised domain-adaptive mitochondria segmentation in EM images.
This dataset was split into two subsets, each of which contains 165 image slices of size 768×1,024, for training and testing, respectively
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Instance-Aware Pseudo-Labeling and Class-Focused Contrastive Learning for Weakly Supervised Domain Adaptive Segmentation of Electron Microscopy
A multitask learning method with instance-aware pseudo-labeling and class-focused contrastive learning outperforms prior UDA and WDA techniques for weakly supervised domain-adaptive mitochondria segmentation in EM images.