AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is suggested that combining complementary pretrained representations can improve histopathological classification when annotations are limited, and FFM-CP achieves higher mean macro-F1 than the strongest individually adapted member of each fused set in 50 of 54 comparisons.
A Dynamic Uncertainty-aware Network (DynU-Net) is proposed, a multi-task framework that adaptively balances segmentation and classification through learnable per-task uncertainty parameters that consistently outperforms both single-task and existing multi-task baselines.
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