AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper synthesizes reported evidence on ZTA across three research questions: effectiveness relative to perimeter models, the implementation challenges enterprises face, and the security contribution of individual components.
A computationally efficient skin lesion classification framework for seven classes using EfficientNet-B0, complemented by Monte Carlo (MC) Dropout for uncertainty quantification is introduced, and the only lightweight method in the comparison providing calibrated uncertainty estimates.
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