AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work provides a data-driven framework for configuring detectors on UAVs, enabling practitioners to maximize performance for specific mission profiles and enhancing the reliability of autonomous search systems.
A hybrid Multi-Layer Perceptron (MLP)–XGBoost model for heart disease prediction is proposed, combining the feature extraction capability of neural networks with the ensemble robustness of gradient boosting to enhance both predictive accuracy and reliability for cardiovascular disease diagnosis.
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