AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The Integrated Forward-Inverse Network (IFIN) is proposed, a physics-guided architecture that interleaves differentiable forward projections with learnable inverse updates at every scale, enabling complementary cues to be exploited jointly in the measurement and image domains.
The Bifurcated Speckle Network is introduced, a hybrid deep learning architecture that merges empirical data training with analytical physical models to mitigate noise artifacts of undersampled speckle measurements in RSSI and accelerates accurate flow parameter estimation for continuous biological monitoring.
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