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Preface -- AI and machine learning for real-world problems -- Survey of graph neural network for learning complex problems -- Adaptive software platform architecture for aerial vehicle safety levels in real-world applications -- OODA loop for learning open-world novelty problems -- Privacy-aware crowd counting methods for real-world environment -- AI and machine learning for computer vision applications in open world -- PIM hardware accelerators for real-world problems -- Irregular situations in real-world intelligent systems -- Offline reinforcement learning methods for real-world problems -- Addressing uncertainty challenges for autonomous driving in real-world environments.
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Online resource; title from home page (ScienceDirect, viewed March 4, 2024).
