2020 2nd Ieee International Conference On Artificial Intelligence Circuits And Systems Aicas

Artificial Intelligence is driving a new revolution in domains ranging from manufacturing, automotive, healthcare, robotics, entertainment, and many others New computing platforms are required to support the emerging AI algorithms and applications, from cloud servers to edge devices, from system level to circuit level AICAS facilitates research, innovation and development activities at the frontiers of circuits and systems for AI It allows academia to meet industry from the international community to exchange experiences, demonstrate their studies and further advance AI technologies AICAS is the major conference for AI that stands between theory, applications, and ASICs The theme of AICAS2020 is Circuits and systems for efficient embedded AI , revolving around the development of hardware and computational strategies towards an increase in system efficiency that supports efficient, embedded, smart applications (such as mobile, robotics, automotive)

Circuits and systems for AI Deep learning machine learning AI algorithms Tools platforms for AI Architecture for AI computing Hardware software co design and design automation for AI systems Advanced neural network design Neuromorphic circuits, processors, and systems and their applications Emerging applications Internet of things, healthcare, smart factories, environment Emerging devices and materials for AI Computer vision algorithms and architectures Recommendation system, language text processing Autonomous unmanned vehicles and drone Robotics and automation Metaverse and AR VR Deep learning machine learning for Future Wireless Communications

Circuits and systems for AI Deep learning machine learning AI algorithms Tools Platforms for AI Architectures for AI computing Neuromorphic circuits, processors and systems and their applications Hardware software co design and design automation for AI systems Advanced neural network design Emerging applications Internet of Things, healthcare, autonomous vehicles, environment Emerging devices and materials for AI

Artificial Intelligence is driving a new revolution in domains ranging from manufacturing, automotive, healthcare, robotics, entertainment, and many others New computing platforms are required to support the emerging AI algorithms and applications, from cloud servers to edge devices, from system level to circuit level AICAS facilitates research, innovation and development activities at the frontiers of circuits and systems for AI It allows academia to meet industry from the international community to exchange experiences, demonstrate their studies and further advance AI technologies AICAS is the major conference for AI that stands between theory, applications, and ASICs

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 12532, is organized in topical sections on human-computer interaction; image processing and computer vision; natural language processing.

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence

This book showcases the state of the art in the field of electronics, as presented by researchers and engineers at the 54th Annual Meeting of the Italian Electronics Society (SIE), held in Noto (SR), Italy, on September 6–8, 2023. It covers a broad range of aspects, including: integrated circuits and systems, micro- and nano-electronic devices, microwave electronics, sensors and microsystems, optoelectronics and photonics, power electronics, electronic systems and applications.

This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence. The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needs Amitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India. Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India. Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.