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Computer Analysis of Images and Patterns
This volume LNCS 14184 and 14185 constitutes the refereed proceedings of the 20th International Conference, CAIP 2023, in Limassol, Cyprus, in September 2023. The 54 full papers presented were carefully reviewed and selected from 67 submissions. They were organized in the following section as follows: Part I: PAR Contest 2023; Deep Learning; Machine Learning for Image and Pattern Analysis; and Object Recognition and Segmentation. Part II : Biometrics- Human Pose Estimation- Action Recognition; Biomedical Image and Pattern Analysis; and General Vision- AI Applications.
Proceedings of the 4th International Conference on Electrical Engineering and Control Applications
This book gathers papers presented during the 4th International Conference on Electrical Engineering and Control Applications. It covers new control system models, troubleshooting tips and complex system requirements, such as increased speed, precision and remote capabilities. Additionally, the papers discuss not only the engineering aspects of signal processing and various practical issues in the broad field of information transmission, but also novel technologies for communication networks and modern antenna design. This book is intended for researchers, engineers and advanced postgraduate students in the fields of control and electrical engineering, computer science and signal processing, as well as mechanical and chemical engineering.
Computer Vision – ECCV 2022
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.
Heterogeneous Cyber Physical Systems of Systems
Cyber-physical systems are the natural extension of the so-called “Internet of Things”. They are “systems of collaborating computational elements controlling physical entities”. Cyber Physical Systems of Systems (CPSoS) are considered “The Next Computing Revolution” after Mainframe computing (60’s-70’s), Desktop computing & Internet (80’s-90’s) and Ubiquitous computing (00’s); because all aspects of daily life are rapidly evolving towards humans interacting amongst themselves as well as their environment via computational devices (often mobile), and because in most cases systems will employ their computational capabilities to interact amongst themselves.CPSoS enable the...
Energy Efficiency and Robustness of Advanced Machine Learning Architectures
Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing for a single objective/have a limited set of goals. This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks. More specifically, this book improves the energy efficiency of complex m...
Next Generation Multiple Access
Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies. The scope and depth of this book are balanced for both beginners to advanced users. Additional refe...
