Artificial Intelligence and Machine Learning for Open-world Novelty: Volume 134 - Rilegato

Deka

Rilegato

ISBN 10: 032399928X ISBN 13: 9780323999281

Casa editrice: Academic Press, 2024

Riassunto

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.

Su questo libro

Informazioni sugli autori

Ganesh Chandra Deka is currently Deputy Director (Training) at Directorate General of Training, Ministry of Skill Development and Entrepreneurship, Government of India, New Delhi-110001, India. His research interests include e-Governance, Big Data Analytics, NoSQL Databases and Vocational Education and Training.

He has 2 books on Cloud Computing published by LAP Lambert, Germany. He is the Co-author for 4 text books on Fundamentals of Computer Science (3 books published by Moni Manik Prakashan, Guwahati, Assam, India and 1 IGI Global, USA). As of now he has edited 14 books (6 IGI Global, USA, 5 CRC Press, USA, 2 Elsevier & 1 Springer) on Big data, NoSQL and Cloud Computing and authored 10 Book Chapters.

He has published around 47 research papers in various IEEE conferences. He has organized 08 IEEE International Conferences as Technical Chair in India. He is the Member of the editorial board and reviewer for various Journals and International conferences. Member of IEEE, the Institution of Electronics and Telecommunication Engineers, India and Associate Member, the Institution of Engineers, India

Shiho Kim is a professor in the school of integrated technology at Yonsei University, Seoul, Korea. His previous assignment includes, System on chip design engineer, at LG Semicon Ltd. (currently SK Hynix), Korea, Seoul [1995-1996], Director of RAVERS (Research center for Advanced Hybrid Electric Vehicle Energy Recovery System, a government-supported IT research center. Associate Director of the ICT consilience program, which is a Korea National program for cultivating talented engineers in the field of information and communication Technology, Korea [2011-2012], Director of Seamless Transportation Lab, at Yonsei university, Korea [since 2011-]. His main research interest includes Development of software and hardware technologies for intelligent vehicles, Blockchain technology for intelligent transportation systems, and reinforcement learning for autonomous vehicles. He is the member of the editorial board and reviewer for various Journals and International conferences. So far he has organized 2 International Conference as Technical Chair/General Chair. He is a member of IEIE (Institute of Electronics and Information Engineers of Korea), KSAE (Korean Society of Automotive Engineers), vice president of KINGC (Korean Institute of Next Generation Computing), and a senior member of IEEE. He is the co-author for over 100 papers and holding more than 50 patents in the area of information and communication technology.

Dettagli dell?edizione

• Editore: Academic Press
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 032399928X
• ISBN 13: 9780323999281
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 376
• Contatto del produttore: Academic Press; https://shop.elsevier.com/; ; 230 PARK AVENUE, SUITE 800; NY; NY; 10169; U.S.A.
• Persona responsabile: non disponibile