AMN fuses Swin Transformer and ResNet-50 via adaptive gating and trains with focal, boundary, and uncertainty losses to reach 0.82 mean Dice on the seven-class CoNIC benchmark.
ChatGPT in healthcare: A taxonomy and systematic review
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AMN: An Adaptive Multi-Scale Fusion Network with Boundary and Uncertainty Modeling for Nuclei Segmentation
AMN fuses Swin Transformer and ResNet-50 via adaptive gating and trains with focal, boundary, and uncertainty losses to reach 0.82 mean Dice on the seven-class CoNIC benchmark.
- LLM Harms: A Taxonomy and Discussion