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Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part IX (Lecture Notes in Computer Science #14262)

by Lazaros Iliadis Antonios Papaleonidas Plamen Angelov Chrisina Jayne

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers and 9 short papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14254)

by Lazaros Iliadis Antonios Papaleonidas Plamen Angelov Chrisina Jayne

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part VII (Lecture Notes in Computer Science #14260)

by Lazaros Iliadis Antonios Papaleonidas Plamen Angelov Chrisina Jayne

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part VIII (Lecture Notes in Computer Science #14261)

by Lazaros Iliadis Antonios Papaleonidas Plamen Angelov Chrisina Jayne

The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Artificial Neural Networks and Structural Equation Modeling: Marketing and Consumer Research Applications

by Alhamzah Alnoor Khaw Khai Wah Azizul Hassan

This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the black box technology of artificial intelligence. Hence, the ANN approach validates the results of the SEM method. In addition, such the novel emerging approach increases the validity of the prediction by determining the importance of the variables. Consequently, the number of studies using SEM-ANN has increased, but the different types of study cases that show customization of different processes in ANNs method combination with SEM are still unknown, and this aspect will be affecting to the generation results. Thus, there is a need for further investigation in marketing and consumer research. This book bridges the significant gap in this research area. The adoption of SEM and ANN techniques in social commerce and consumer research is massive all over the world. Such an expansion has generated more need to learn how to capture linear and non-compensatory relationships in such area. This book would be a valuable reading companion mainly for business and management students in higher academic organizations, professionals, policy-makers, and planners in the field of marketing. This book would also be appreciated by researchers who are keenly interested in social commerce and consumer research.

Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations

by S. Chakraverty Susmita Mall

Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This book shows how computation of differential equation becomes faster once the ANN model is properly developed and applied.

Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

by R. N. G. Naguib G. V. Sherbet

The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril

Artificial Neural Networks in Pattern Recognition: 10th IAPR TC3 Workshop, ANNPR 2022, Dubai, United Arab Emirates, November 24–26, 2022, Proceedings (Lecture Notes in Computer Science #13739)

by Neamat El Gayar Edmondo Trentin Mirco Ravanelli Hazem Abbas

This book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2022, held in Dubai, UAE, in November 2022. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The conference presents papers on subject such as pattern recognition and machine learning based on artificial neural networks.

Artificial Neural Networks in Pattern Recognition: 7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28–30, 2016, Proceedings (Lecture Notes in Computer Science #9896)

by Friedhelm Schwenker Hazem M. Abbas Neamat El Gayar Edmondo Trentin

Artificial Neural Networks in Pattern Recognition synthesizes the proceedings of the 4th IAPR TC3 Workshop, ANNPR 2010. Topics include supervised and unsupervised learning, feature selection, pattern recognition in signal and image processing.

Artificial Neural Networks in Pattern Recognition: 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020, Proceedings (Lecture Notes in Computer Science #12294)

by Thilo Stadelmann Frank-Peter Schilling

This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.

Artificial Neural Networks in Pattern Recognition: 8th Iapr Tc3 Workshop, Annpr 2018, Siena, Italy, September 19-21, 2018, Proceedings (Lecture Notes in Computer Science #11081)

by Edmondo Trentin Friedhelm Schwenker Luca Pancioni

This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018.The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Artificial Neural Networks with Java: Tools For Building Neural Network Applications

by Igor Livshin

Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural network processing. Artificial Neural Networks with Java also teaches you how to prepare the data to be used in neural network development and suggests various techniques of data preparation for many unconventional tasks. <P><P> The next big topic discussed in the book is using Java for neural network processing. You will use the Encog Java framework and discover how to do rapid development with Encog, allowing you to create large-scale neural network applications. <P><P> The book also discusses the inability of neural networks to approximate complex non-continuous functions, and it introduces the micro-batch method that solves this issue. The step-by-step approach includes plenty of examples, diagrams, and screen shots to help you grasp the concepts quickly and easily.

Artificial Neural Networks with Java: Tools for Building Neural Network Applications

by Igor Livshin

Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions. In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision. It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution. The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily.What You Will LearnUse Java for the development of neural network applicationsPrepare data for many different tasksCarry out some unusual neural network processingUse a neural network to process non-continuous functionsDevelop a program that recognizes handwritten digitsWho This Book Is ForIntermediate machine learning and deep learning developers who are interested in switching to Java

Artificial Neural Networks with TensorFlow 2: ANN Architecture Machine Learning Projects

by Poornachandra Sarang

Develop machine learning models across various domains. This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.After learning what's new in TensorFlow 2, you'll dive right into developing machine learning models through applicable projects. This book covers a wide variety of ANN architectures—starting from working with a simple sequential network to advanced CNN, RNN, LSTM, DCGAN, and so on. A full chapter is devoted to each kind of network and each chapter consists of a full project describing the network architecture used, the theory behind that architecture, what data set is used, the pre-processing of data, model training, testing and performance optimizations, and analysis. This practical approach can either be used from the beginning through to the end or, if you're already familiar with basic ML models, you can dive right into the application that interests you. Line-by-line explanations on major code segments help to fill in the details as you work and the entire project source is available to you online for learning and further experimentation. With Artificial Neural Networks with TensorFlow 2 you'll see just how wide the range of TensorFlow's capabilities are. What You'll LearnDevelop Machine Learning ApplicationsTranslate languages using neural networksCompose images with style transferWho This Book Is ForBeginners, practitioners, and hard-cored developers who want to master machine and deep learning with TensorFlow 2. The reader should have working concepts of ML basics and terminologies.

Artificial or Constructed Wetlands: A Suitable Technology for Sustainable Water Management

by María del Durán-Domínguez-de-Bazúa Amado Enrique Navarro-Frómeta Josep M. Bayona

Artificial or constructed wetlands are an emerging technology particularly for tropical areas with water scarcity. For big cities, the sustainable management of water resources taking into account proper use is always challenging. The book presents case studies illustrating the above. As plants and microorganisms are a fundamental part of the correct functioning of these systems, their contribution to the degradation of the organic matter and to the removal and transformation of the pollutant compounds present in the wastewaters is also a highlight of this book.

Artificial Organ Engineering

by Luigi Marrelli Vincenzo Piemonte Maria Cristina Annesini Luca Turchetti

Artificial organs may be considered as small-scale process plants, in which heat, mass and momentum transfer operations and, possibly, chemical transformations are carried out. This book proposes a novel analysis of artificial organs based on the typical bottom-up approach used in process engineering. Starting from a description of the fundamental physico-chemical phenomena involved in the process, the whole system is rebuilt as an interconnected ensemble of elemental unit operations. Each artificial organ is presented with a short introduction provided by expert clinicians. Devices commonly used in clinical practice are reviewed and their performance is assessed and compared by using a mathematical model based approach. Whilst mathematical modelling is a fundamental tool for quantitative descriptions of clinical devices, models are kept simple to remain focused on the essential features of each process. Postgraduate students and researchers in the field of chemical and biomedical engineering will find that this book provides a novel and useful tool for the analysis of existing devices and, possibly, the design of new ones. This approach will also be useful for medical researchers who want to get a deeper insight into the basic working principles of artificial organs.

Artificial Organic Networks: Artificial Intelligence Based on Carbon Networks (Studies in Computational Intelligence #521)

by Hiram Ponce-Espinosa Pedro Ponce-Cruz Arturo Molina

This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEW(tm) toolkit, downloadable from the book's page at springer. com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.

Artificial Organs (New Techniques in Surgery Series #4)

by Nadey S. Hakim

This book deals with organ failure and the way it can be managed artificially without requiring a transplant. Written by a mixture of European and US physicians and surgeons, each of the chapters compares the artificial organ to what is currently available from the transplant point of view to highlight the current and modern available techniques for organ replacement. The book will be a useful reading for postgraduate students and people interested in modern surgical and medical technology.

Artificial Parts, Practical Lives: Modern Histories of Prosthetics

by Katherine Ott David Serlin Stephen Mihm

These essays are valuable first forays into the history of prosthetics. From the wooden teeth of George Washington to the Bly prosthesis, popular in the 1860s and boasting easy uniform motions of the limb, to today's lifelike approximations, prosthetic devices reveal the extent to which the evolution and design of technologies of the body are intertwined with both the practical and subjective needs of human beings. The peculiar history of prosthetic devices sheds light on the relationship between technological change and the civilizing process of modernity, and analyzes the concrete materials of prosthetics which carry with them ideologies of body, ideals, body politics, and culture. Simultaneously critiquing, historicizing, and theorizing prosthetics, Artificial Parts, Practical Lives lays out a balanced and complex picture of its subject, neither vilifying nor celebrating the merger of flesh and machine.

Artificial Parts, Practical Lives: Modern Histories of Prosthetics

by Katherine Ott David Serlin Stephen Mihm

From the wooden teeth of George Washington to the Bly prosthesis, popular in the 1860s and boasting easy uniform motions of the limb, to today's lifelike approximations, prosthetic devices reveal the extent to which the evolution and design of technologies of the body are intertwined with both the practical and subjective needs of human beings. The peculiar history of prosthetic devices sheds light on the relationship between technological change and the civilizing process of modernity, and analyzes the concrete materials of prosthetics which carry with them ideologies of body, ideals, body politics, and culture. Simultaneously critiquing, historicizing, and theorizing prosthetics, Artificial Parts, Practical Lives lays out a balanced and complex picture of its subject, neither vilifying nor celebrating the merger of flesh and machine.

Artificial Psychology: Psychological Modeling and Testing of AI Systems

by James A. Crowder John Carbone Shelli Friess

This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling.Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems;Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future;Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving;Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.

Artificial Psychology: The Quest for What It Means to Be Human

by Jay Friedenberg

Is it possible to construct an artificial person? Researchers in the field of artificial intelligence have for decades been developing computer programs that emulate human intelligence. This book goes beyond intelligence and describes how close we are to recreating many of the other capacities that make us human. These abilities include learning, creativity, consciousness, and emotion. The attempt to understand and engineer these abilities constitutes the new interdisciplinary field of artificial psychology, which is characterized by contributions from philosophy, cognitive psychology, neuroscience, computer science, and robotics. This work is intended for use as a main or supplementary introductory textbook for a course in cognitive psychology, cognitive science, artificial intelligence, or the philosophy of mind. It examines human abilities as operating requirements that an artificial person must have and analyzes them from a multidisciplinary approach. The book is comprehensive in scope, covering traditional topics like perception, memory, and problem solving. However, it also describes recent advances in the study of free will, ethical behavior, affective architectures, social robots, and hybrid human-machine societies.

Artificial Rearing of Reduviid Predators for Pest Management

by K. Sahayaraj R. Balasubramanian

This eye-opening book focuses on the development of techniques to mass-produce reduviid predators and important generalist predators, an endeavor that won't prove sufficient if the cost of commercialization is prohibitive. Advancing mass production to the level of economic feasibility is critical, so that these new technologies can compete in the open market. This book commences with a review of the diversity of reduviid predators in agro-ecosystems world-wide, followed by chapters on their feeding behavior, biology, gut microbiota, their enzyme profile, body protein and genomics, and DNA and field evaluation reports. The field evaluation of reduviids, a worldwide undertaking, is addressed in the last chapter. Each chapter includes a separate conclusion and future recommendations. Detailed information is also included on ingredients and artificial diet preparation, storage and the impact on predators. The artificial rearing of reduviid predator for crop pest management is an essential reference and teaching tool for teachers, researchers and extension workers in developed and developing countries alike, allowing them to produce reduviid predators and important natural enemies in biocontrol and bio-intensive integrated pest management programs. The book offers an excellent resource for all those who are working on beneficial arthropod mass production. It is also an essential reference guide for agricultural and biological sciences scientists, entomologists, crop protection specialists, extension workers, and consultants.

Artificial Receptors for Chemical Sensors

by Vladimir M. Mirsky Anatoly K. Yatsimirsky

The first to provide systematically organized information on all three important aspects of artificial receptor design, this book brings together knowledge on an exceptionally hot and multidisciplinary field of research. Strong emphasis is placed on the methodology for discovering artificial receptors, with both definitions for chemosensitivity as well as experimental setups supplied. There follows coverage of numerous classes of artificial receptors, including synthesis, immobilization on surfaces, and quantitative data on properties. The third part of the book focuses on receptor arrays for artificial nose and tongue applications and the whole is rounded off with an outlook and an appendix with all relevant quantitative data on artificial receptors.

Artificial Reefs: Marine and Freshwater Applications

by Frank M. D'itri

In this book fisheries biologists, ecologists, limnologists, oceanographers, aquatic resource managers and planners, commercial fisherman and environmental scientists are offered information on the latest artificial fishing reef designs, siting and placement methods, and ecological research as well as an overview of current united states legislation and regulations.

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