AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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AgriCountDINO, a parameter-efficient exemplar-guided framework for joint counting and localization, is introduced, a parameter-efficient exemplar-guided framework for joint counting and localization that improves upon the best compared zero-shot method by 6.0\% without target-domain training or fine-tuning.
A 3D U-Net-based segmentation framework, NeuroFocusNet, which synchronizes spatial attention, channel recalibration, and attention-gated skip connections within a single volumetric encoder-decoder model is proposed, which is encouraging when considering the feasibility of using NeuroFocusNet as a technically promising...
A comprehensive analysis of the performance-forgetting trade-offs inherent in low-rank adaptation using principal components of weight matrices as initialization reveals that fine-tuning intermediate components leads to better balance and robustness to high learning rates than first (PiSSA) and last (MiLoRA) components...
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