Multidisciplinary Approaches to Neural Computing

Multidisciplinary Approaches to Neural Computing PDF Author: Anna Esposito
Publisher: Springer
ISBN: 331956904X
Category : Technology & Engineering
Languages : en
Pages : 380

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Book Description
This book presents a collection of contributions in the field of Artificial Neural Networks (ANNs). The themes addressed are multidisciplinary in nature, and closely connected in their ultimate aim to identify features from dynamic realistic signal exchanges and invariant machine representations that can be exploited to improve the quality of life of their end users. Mathematical tools like ANNs are currently exploited in many scientific domains because of their solid theoretical background and effectiveness in providing solutions to many demanding tasks such as appropriately processing (both for extracting features and recognizing) mono- and bi-dimensional dynamic signals, solving strong nonlinearities in the data and providing general solutions for deep and fully connected architectures. Given the multidisciplinary nature of their use and the interdisciplinary characterization of the problems they are applied to – which range from medicine to psychology, industrial and social robotics, computer vision, and signal processing (among many others) – ANNs may provide a basis for redefining the concept of information processing. These reflections are supported by theoretical models and applications presented in the chapters of this book. This book is of primary importance for: (a) the academic research community, (b) the ICT market, (c) PhD students and early-stage researchers, (d) schools, hospitals, rehabilitation and assisted-living centers, and (e) representatives of multimedia industries and standardization bodies.

Handbook of Neural Computation

Handbook of Neural Computation PDF Author: Pijush Samui
Publisher: Academic Press
ISBN: 0128113197
Category : Technology & Engineering
Languages : en
Pages : 660

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Book Description
Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Theoretical Advances in Neural Computation and Learning

Theoretical Advances in Neural Computation and Learning PDF Author: Vwani Roychowdhury
Publisher: Springer Science & Business Media
ISBN: 1461526965
Category : Computers
Languages : en
Pages : 482

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Book Description
For any research field to have a lasting impact, there must be a firm theoretical foundation. Neural networks research is no exception. Some of the founda tional concepts, established several decades ago, led to the early promise of developing machines exhibiting intelligence. The motivation for studying such machines comes from the fact that the brain is far more efficient in visual processing and speech recognition than existing computers. Undoubtedly, neu robiological systems employ very different computational principles. The study of artificial neural networks aims at understanding these computational prin ciples and applying them in the solutions of engineering problems. Due to the recent advances in both device technology and computational science, we are currently witnessing an explosive growth in the studies of neural networks and their applications. It may take many years before we have a complete understanding about the mechanisms of neural systems. Before this ultimate goal can be achieved, an swers are needed to important fundamental questions such as (a) what can neu ral networks do that traditional computing techniques cannot, (b) how does the complexity of the network for an application relate to the complexity of that problem, and (c) how much training data are required for the resulting network to learn properly? Everyone working in the field has attempted to answer these questions, but general solutions remain elusive. However, encouraging progress in studying specific neural models has been made by researchers from various disciplines.

Advances in Neural Computation, Machine Learning, and Cognitive Research

Advances in Neural Computation, Machine Learning, and Cognitive Research PDF Author: Boris Kryzhanovsky
Publisher: Springer
ISBN: 9783319882833
Category : Computers
Languages : en
Pages : 199

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Book Description
This book describes new theories and applications of artificial neural networks, with a special focus on neural computation, cognitive science and machine learning. It discusses cutting-edge research at the intersection between different fields, from topics such as cognition and behavior, motivation and emotions, to neurocomputing, deep learning, classification and clustering. Further topics include signal processing methods, robotics and neurobionics, and computer vision alike. The book includes selected papers from the XIX International Conference on Neuroinformatics, held on October 2-6, 2017, in Moscow, Russia.

Applications of Computational Intelligence in Multi-Disciplinary Research

Applications of Computational Intelligence in Multi-Disciplinary Research PDF Author: Ahmed A. Elngar
Publisher: Academic Press
ISBN: 0128241764
Category : Science
Languages : en
Pages : 222

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Book Description
Applications of Computational Intelligence in Multi-Disciplinary Research provides the readers with a comprehensive handbook for applying the powerful principles, concepts, and algorithms of computational intelligence to a wide spectrum of research cases. The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing. Other key approaches included are swarm intelligence and artificial immune systems. These approaches provide researchers with powerful tools for analysis and problem-solving when data is incomplete and when the problem under consideration is too complex for standard mathematics and the crisp logic approach of Boolean computing. - Provides an overview of the key methods of computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods - Includes case studies and real-world examples of computational intelligence applied in a variety of research topics, including bioinformatics, biomedical engineering, big data analytics, information security, signal processing, machine learning, nanotechnology, and optimization techniques - Presents a thorough technical explanation on how computational intelligence is applied that is suitable for a wide range of multidisciplinary and interdisciplinary research

Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning

Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning PDF Author: Habib, Maki K.
Publisher: IGI Global
ISBN: 1799886875
Category : Computers
Languages : en
Pages : 589

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Book Description
As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.

Multidisciplinary Approach to Information Technology in Library and Information Science

Multidisciplinary Approach to Information Technology in Library and Information Science PDF Author: Holland, Barbara
Publisher: IGI Global
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 362

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Book Description
In the ever-evolving landscape of information technology within library and information science, scholars often find themselves navigating a complex web of diverse research areas. The broad spectrum of topics, ranging from digital libraries to artificial intelligence, poses a significant challenge for academic scholars seeking a comprehensive understanding of the field's intricacies. The absence of a consolidated resource tailored to the specific needs of graduate students, professors, and practitioners further exacerbates this issue. Multidisciplinary Approach to Information Technology in Library and Information Science addresses the pressing challenges faced by scholars in the realm of library and information science. This reference handbook serves as a beacon, illuminating the multifaceted interactions and impacts of technologies on information resources. This book delves into the ethical, legal, and social implications of information technology across diverse contexts – libraries, information centers, archives, museums, education, business, government, and healthcare.

Computer Security – ESORICS 2024

Computer Security – ESORICS 2024 PDF Author: Joaquin Garcia-Alfaro
Publisher: Springer Nature
ISBN: 3031708792
Category :
Languages : en
Pages : 411

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Book Description


ICT Analysis and Applications

ICT Analysis and Applications PDF Author: Simon Fong
Publisher: Springer Nature
ISBN: 9811583544
Category : Technology & Engineering
Languages : en
Pages : 817

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Book Description
This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 5th International Conference on ICT for Sustainable Development (ICT4SD 2020), held in Goa, India, on 23–24 July 2020. The conference provided a valuable forum for cutting-edge research discussions among pioneering researchers, scientists, industrial engineers, and students from all around the world. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.

Bio-inspired Neurocomputing

Bio-inspired Neurocomputing PDF Author: Akash Kumar Bhoi
Publisher: Springer Nature
ISBN: 9811554951
Category : Technology & Engineering
Languages : en
Pages : 427

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Book Description
This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.