Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into artificial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.
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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.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Englisch. N° de réf. du vendeur 9780128231234
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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. N° de réf. du vendeur 9780128231234
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