The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
JCNN is the premier international conference on neural networks theory, analysis, and a wide range of applications IJCNN 2021 is a truly interdisciplinary event with a broad range of contributions on recent advances in neural networks, including neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, bioinformatics and biomedicine, and engineering applications
With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern computational intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using data science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, covering the entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations.
This book covers the following main topics: A) information and knowledge management; B) organizational models and information systems; C) software and systems modeling; D) software systems, architectures, applications and tools; E) multimedia systems and applications; F) computer networks, mobility and pervasive systems; G) intelligent and decision support systems; H) big data analytics and applications; I) human–computer interaction; J) ethics, computers and security; K) health informatics; L) information technologies in education; M) information technologies in radio communications; N) technologies for biomedical applications. This book is composed by a selection of articles from The 2022 World Conference on Information Systems and Technologies (WorldCIST'22), held between April 12 and 14, in Budva, Montenegro. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences, and challenges of modern information systems and technologies research, together with their technological development and applications.
Methods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.
The present book brings together experience, current work, and promising future trends associated with distributed computing, artificial intelligence, and their application in order to provide efficient solutions to real problems. DCAI 2023 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 108 papers were submitted, by authors from 31 different countries representing a truly “wide area network” of research activity. The DCAI 23 technical program has selected 36 full papers in the main track and, as in past editions, there will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors like to thank all the contributing authors, the members of the Program Committee, National Associations (AEPIA, APPIA), and the sponsors (AIR Institute).
This book gathers the proceedings of the eighth Future of Information and Computing Conference, which was held successfully in virtual mode. It received a total of 369 paper submissions from renowned and budding scholars, academics, and distinguished members of the industry. The topics fanned across various fields involving computing, Internet of Things, data science, and artificial intelligence. Learned scholars from all walks of life assembled under one roof to share their unique, original, and breakthrough researches and paved a new technological path for the world. Many of the studies seek to change the face of the world itself. Their innovative thinking indeed aims to solve several gruesome problems in the field of communication, data science, ambient intelligence, networking, computing, security, and privacy. The authors have strived to render valuable pieces of study in this edition and hope to acquire enthusiastic support from the readers.
This book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users.
