AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Noise residual fingerprints are extracted by a simple yet effective pre-trained Noiseprint++ model, outperforming the state-of-the-art detectors on generalization ability, and the effectiveness of each module is validated by ablation studies.
This work proposes RNSIDNet, a novel forensic framework that achieves robust detection through enhanced RGB-Noise representation learning, and designs a Hard Sample-aware Contrastive Learning (HSCL) strategy.
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