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most citedEnhancing Weakly-Supervised Histopathology Image Segmentation with Knowledge Distillation on MIL-Based Pseudo-Labels

2 citations · 2 across the 8 of their papers we have counts for

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cs.CV2024★ 2 cited

Enhancing Weakly-Supervised Histopathology Image Segmentation with Knowledge Distillation on MIL-Based Pseudo-Labels

Yinsheng He, Xingyu Li, Roger J. Zemp

Segmenting tumors in histological images is vital for cancer diagnosis. While fully supervised models excel with pixel-level annotations, creating such annotations is labor-intensi…