Artificial Intelligence Applications in Information and Communication Technologies
Artificial Intelligence Applications in Information and Communication Technologies

Author: Yacine Laalaoui

Publisher: Springer

Published: 2015-07-04

Total Pages: 216

ISBN-13: 3319198335

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This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.

Recent Advances in Information and Communication Technology 2020
Recent Advances in Information and Communication Technology 2020

Author: Phayung Meesad

Publisher: Springer Nature

Published: 2020-03-21

Total Pages: 220

ISBN-13: 3030440443

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This book gathers the proceedings of the 16th International Conference on Computing and Information Technology (IC2IT 2020), held on May 14th–15th, 2020, at Dusit Thani Pattaya, Thailand. The topics covered include big data, artificial intelligence, machine learning, natural language processing, speech recognition, image and video processing, and deep learning. In turn, the topics represent major research and engineering directions for autonomous driving, language assistants, automatic translation, and answering systems. Lastly, they are responses to major economic changes around the world, which are increasingly shaped by the need for enhanced globalization and worldwide cooperation, and by emerging global problems.

Advances in Cybernetics, Cognition, and Machine Learning for Communication Technologies
Advances in Cybernetics, Cognition, and Machine Learning for Communication Technologies

Author: Vinit Kumar Gunjan

Publisher: Springer

Published: 2021-04-29

Total Pages: 0

ISBN-13: 9789811531279

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This book highlights recent advances in Cybernetics, Machine Learning and Cognitive Science applied to Communications Engineering and Technologies, and presents high-quality research conducted by experts in this area. It provides a valuable reference guide for students, researchers and industry practitioners who want to keep abreast of the latest developments in this dynamic, exciting and interesting research field of communication engineering, driven by next-generation IT-enabled techniques. The book will also benefit practitioners whose work involves the development of communication systems using advanced cybernetics, data processing, swarm intelligence and cyber-physical systems; applied mathematicians; and developers of embedded and real-time systems. Moreover, it shares insights into applying concepts from Machine Learning, Cognitive Science, Cybernetics and other areas of artificial intelligence to wireless and mobile systems, control systems and biomedical engineering.

Information and Communication Technologies for Development Evaluation
Information and Communication Technologies for Development Evaluation

Author: Oscar A. García

Publisher: Routledge

Published: 2019-07-09

Total Pages: 173

ISBN-13: 042965054X

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Written by a team of expert practitioners at the Independent Office of Evaluation of International Fund for Agricultural Development (IFAD), this book gives an insight into the implications of new and emerging technologies in development evaluation. Growing technologies such as big data analytics, machine learning and remote sensing present new opportunities for development practitioners and development evaluators, particularly when measuring indicators of the Sustainable Development Goals. The volume provides an overview of information and communication technologies (ICTs) in the context of evaluation, looking at the theory and practice, and discussing how the landscape may unfold. It also considers concerns about privacy, ethics and inclusion, which are crucial issues for development practitioners and evaluators working in the interests of vulnerable populations across the globe. Among the contributions are case studies of seven organizations using various technologies for data collection, analysis, dissemination and learning. This valuable insight into practice will be of interest to researchers, practitioners and policymakers in development economics, development policy and ICT.

Machine Learning and Wireless Communications
Machine Learning and Wireless Communications

Author: Yonina C. Eldar

Publisher: Cambridge University Press

Published: 2022-06-30

Total Pages: 560

ISBN-13: 1108967736

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How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Deep Learning and Parallel Computing Environment for Bioengineering Systems
Deep Learning and Parallel Computing Environment for Bioengineering Systems

Author: Arun Kumar Sangaiah

Publisher: Academic Press

Published: 2019-07-26

Total Pages: 282

ISBN-13: 0128172932

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Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data

Artificial Intelligence and Machine Learning for Business for Non-Engineers
Artificial Intelligence and Machine Learning for Business for Non-Engineers

Author: Stephan S. Jones

Publisher: CRC Press

Published: 2019-11-22

Total Pages: 165

ISBN-13: 1000733653

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The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI’s current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry.

Artificial Intelligence in Information and Communication Technologies, Healthcare and Education
Artificial Intelligence in Information and Communication Technologies, Healthcare and Education

Author: Parikshit N Mahalle

Publisher: CRC Press

Published: 2022-12-27

Total Pages: 251

ISBN-13: 1000828913

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Artificial Intelligence in Information and Communication Technologies, Healthcare and Education: A Roadmap Ahead is designed as a reference text and discusses inter-dependability, communication and effective control for the betterment of services through artificial intelligence (AI), as well as the challenges and path ahead for AI in computing and control across different domains of business and human life. The book accommodates technologies and application domains including backbone hardware, systems and methods for deployment, which help incorporating intelligence through different supervised and probabilistic learning approaches. Features The book attempts to establish a connection between hardware, software technologies and algorithmic intelligence for data analysis and decision support in domains such as healthcare, education and other aspects of business and mobility. It presents various recent applications of artificial intelligence in information and communication technologies such as search and optimization methods, machine learning, data representation and ontologies, and multi-agent systems. The book provides a collection of different case studies with experimentation results than mere theoretical and generalized approaches. Covers most of the applications using the trending technologies like machine learning (ML), data science (DS), Internet of Things (IoT), and underlying information and communication technologies. The book is aimed primarily at advanced undergraduates and postgraduate students studying computer science, computer applications, and information technology. Researchers and professionals will also find this book useful.

Information and Communication Technology for Competitive Strategies (ICTCS 2022)
Information and Communication Technology for Competitive Strategies (ICTCS 2022)

Author: Amit Joshi

Publisher: Springer Nature

Published: 2023-05-30

Total Pages: 866

ISBN-13: 9811996385

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This book contains best selected research papers presented at ICTCS 2022: Seventh International Conference on Information and Communication Technology for Competitive Strategies. The conference will be held in Chandigarh, India during 9 – 10 December 2022. The book covers state-of-the-art as well as emerging topics pertaining to ICT and effective strategies for its implementation for engineering and managerial applications. This book contains papers mainly focused on ICT for computation, algorithms and data analytics and IT security. The work is presented in two volumes.

Machine Learning in Computer Vision
Machine Learning in Computer Vision

Author: Nicu Sebe

Publisher: Springer Science & Business Media

Published: 2005-10-04

Total Pages: 253

ISBN-13: 1402032757

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The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.