Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model
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Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model
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Author : Waymond Rodgers
language : en
Publisher: Bentham Science Publishers
Release Date : 2022-07-20
Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model written by Waymond Rodgers and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Computers categories.
This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.
Proceedings Of The 2023 International Conference On Image Algorithms And Artificial Intelligence Iciaai 2023
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Author : Pushpendu Kar
language : en
Publisher: Springer Nature
Release Date : 2023-11-25
Proceedings Of The 2023 International Conference On Image Algorithms And Artificial Intelligence Iciaai 2023 written by Pushpendu Kar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Computers categories.
This is an open access book. Scope of Conference 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI2023), which will be held from August 11 to August 13 in Singapore provides a forum for researchers and experts in different but related fields to discuss research findings. The scope of ICIAAI 2023 covers research areas such as imaging, algorithms and artificial intelligence. Related fields of research include computer software, programming languages, software engineering, computer science applications, artificial intelligence, Intelligent data analysis, deep learning, high-performance computing, signal processing, information systems, computer graphics, computer-aided design, Computer vision, etc. The objectives of the conference are: The conference aims to provide a platform for experts, scholars, engineers and technicians engaged in the research ofimage, algorithm and artificial intelligence to share scientific research results and cutting-edge technologies. The conference will discuss the academic trends and development trends of the related research fields of image, algorithm and artificial intelligence together, carry out discussions on current hot issues, and broaden research ideas. It will be a perfect gathering to strengthen academic research and discussion, promote the development and progress of relevant research and application, and promote the development of disciplines and promote talent training.
Modeling Decisions For Artificial Intelligence
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Author : Vicenc Torra
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-07-22
Modeling Decisions For Artificial Intelligence written by Vicenc Torra and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-22 with Computers categories.
This book constitutes the refereed proceedings of the First International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2004, held in Barcelona, Spain in August 2004. The 26 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 53 submissions. The papers are devoted to topics like models for information fusion, aggregation operators, model selection, fuzzy integrals, fuzzy sets, fuzzy multisets, neural learning, rule-based classification systems, fuzzy association rules, algorithmic learning, diagnosis, text categorization, unsupervised aggregation, the Choquet integral, group decision making, preference relations, vague knowledge processing, etc.
Artificial Intelligence And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer Nature
Release Date : 2023-09-13
Artificial Intelligence And Soft Computing written by Leszek Rutkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-13 with Computers categories.
The two-volume set LNAI 14125 and 14126 constitutes the refereed conference proceedings of the 22nd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2023, held in Zakopane, Poland, during June 18–22, 2023. The 84 revised full papers presented in these proceedings were carefully reviewed and selected from 175 submissions. The papers are organized in the following topical sections: Part I: Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; and Artificial Intelligence in Modeling and Simulation. Part II: Computer Vision, Image and Speech Analysis; Various Problems of Artificial Intelligence; Bioinformatics, Biometrics and Medical Applications; and Data Mining and Pateern Classification.
Intelligent Computing Techniques In Biomedical Imaging
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Author : Bikesh Kumar Singh
language : en
Publisher: Elsevier
Release Date : 2024-08-23
Intelligent Computing Techniques In Biomedical Imaging written by Bikesh Kumar Singh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-23 with Science categories.
Intelligent Computing Techniques in Biomedical Imaging provides comprehensive and state-of-the-art applications of Computational Intelligence techniques used in biomedical image analysis for disease detection and diagnosis. The book offers readers a stepwise approach from fundamental to advanced techniques using real-life medical examples and tutorials. The editors have divided the book into five sections, from prerequisites to case studies.Section I presents the prerequisites, where the reader will find fundamental concepts needed for advanced topics covered later in this book. This primarily includes a thorough introduction to Artificial Intelligence, probability theory and statistical learning. The second section covers Computational Intelligence methods for medical image acquisition and pre-processing for biomedical images. In this section, readers will find AI applied to conventional and advanced biomedical imaging modalities such as X-rays, CT scan, MRI, Mammography, Ultrasound, MR Spectroscopy, Positron Emission Tomography (PET), Ultrasound Elastography, Optical Coherence Tomography (OCT), Functional MRI, Hybrid Modalities, as well as pre-processing topics such as medical image enhancement, segmentation, and compression. Section III covers description and representation of medical images. Here the reader will find various categories of features and their relevance in different medical imaging tasks. This section also discusses feature selection techniques based on filter method, wrapper method, embedded method, and more.The fourth section covers Computational Intelligence techniques used for medical image classification, including Artificial Neural Networks, Support Vector Machines, Decision Trees, Nearest Neighbor Classifiers, Random Forest, clustering, extreme learning, Convolution Neural Networks (CNN), and Recurrent Neural Networks. This section also includes a discussion of computer aided diagnosis and performance evaluation in radiology.The final section of Intelligent Computing Techniques in Biomedical Imaging provides readers with a wealth of real-world Case Studies for Computational Intelligence techniques in applications such as neuro-developmental disorders, brain tumor detection, breast cancer detection, bone fracture detection, pulmonary imaging, thyroid disorders, imaging technologies in dentistry, diagnosis of ocular diseases, cardiovascular imaging, and multimodal imaging. - Introduces Fourier theory and signal analysis tailored to applications in optical communications devices and systems - Provides strong theoretical background, making it a ready resource for researchers and advanced students in optical communication and optical signal processing - Starts from basic theory and then develops descriptions of useful applications
Proceedings Of The International Conference On Artificial Intelligence And Computer Vision Aicv2021
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2021-05-28
Proceedings Of The International Conference On Artificial Intelligence And Computer Vision Aicv2021 written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Technology & Engineering categories.
This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco. This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation, AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.
Artificial Intelligence And Image Processing In Medical Imaging
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Author : Walid A. Zgallai
language : en
Publisher: Elsevier
Release Date : 2024-01-18
Artificial Intelligence And Image Processing In Medical Imaging written by Walid A. Zgallai and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-18 with Science categories.
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. - Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging - Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving - Provides examples of medical imaging and how they're processed, including segmentation, classification, and detection
The Mit Encyclopedia Of The Cognitive Sciences Mitecs
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Author : Robert A. Wilson
language : en
Publisher: MIT Press
Release Date : 2001-09-04
The Mit Encyclopedia Of The Cognitive Sciences Mitecs written by Robert A. Wilson and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-09-04 with Psychology categories.
Since the 1970s the cognitive sciences have offered multidisciplinary ways of understanding the mind and cognition. The MIT Encyclopedia of the Cognitive Sciences (MITECS) is a landmark, comprehensive reference work that represents the methodological and theoretical diversity of this changing field. At the core of the encyclopedia are 471 concise entries, from Acquisition and Adaptationism to Wundt and X-bar Theory. Each article, written by a leading researcher in the field, provides an accessible introduction to an important concept in the cognitive sciences, as well as references or further readings. Six extended essays, which collectively serve as a roadmap to the articles, provide overviews of each of six major areas of cognitive science: Philosophy; Psychology; Neurosciences; Computational Intelligence; Linguistics and Language; and Culture, Cognition, and Evolution. For both students and researchers, MITECS will be an indispensable guide to the current state of the cognitive sciences.
Handbook Of Statistical Analysis
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Author : Robert Nisbet
language : en
Publisher: Elsevier
Release Date : 2024-09-16
Handbook Of Statistical Analysis written by Robert Nisbet and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-16 with Mathematics categories.
Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers, and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business problems, weigh the strengths and weaknesses of modern data analysis algorithms, and employ the right analytical methods for practical application. This resource is an ideal guide for users who want to address massive and complex datasets with many standard analytical approaches and be able to evaluate analyses and solutions objectively. It includes clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques; offers accessible tutorials; and discusses their application to real-world problems. - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data analytics to build successful predictive analytic solutions - Provides in-depth descriptions and directions for performing many data preparation operations necessary to generate data sets in the proper form and format for submission to modeling algorithms - Features clear, intuitive explanations of standard analytical tools and techniques and their practical applications - Provides a number of case studies to guide practitioners in the design of analytical applications to solve real-world problems in their data domain - Offers valuable tutorials on the book webpage with step-by-step instructions on how to use suggested tools to build models - Provides predictive insights into the rapidly expanding "Intelligence Age" as it takes over from the "Information Age," enabling readers to easily transition the book's content into the tools of the future
Art In The Age Of Machine Learning
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Author : Sofian Audry
language : en
Publisher: MIT Press
Release Date : 2021-11-23
Art In The Age Of Machine Learning written by Sofian Audry and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Art categories.
An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.