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Artificial Intelligence and Machine Learning for Open-world Novelty

Ganesh Chandra Deka editor Shiho Kim editor

Format:Hardback

Publisher:Elsevier Science & Technology

Published:19th Feb '24

Should be back in stock very soon

Artificial Intelligence and Machine Learning for Open-world Novelty cover

Artificial Intelligence and Machine Learning for Open-world Novelty, Volume 134 in the Advances in Computers series presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on AI and Machine Learning for Real-world problems, 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 3D Computer Vision Applications in Open-world, and PIM Hardware accelerators for real-world problems. Other sections cover 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, and more.

ISBN: 9780323999281

Dimensions: unknown

Weight: 450g

310 pages