Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications PDF Download

Author: Ruber Hernández-García
Publisher: Springer Nature
ISBN: 3031766040
Category :
Languages : en
Pages : 292

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Author: Pandian Vasant
Publisher: Springer Nature
ISBN: 3031199588
Category : Technology & Engineering
Languages : en
Pages : 1215

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Book Description
This book of Springer Nature is another proof of Springer’s outstanding and greatness on the lively interface of Smart Computational Optimization, Green ICT, Smart Intelligence and Machine Learning! It is a Master Piece of what our community of academics and experts can provide when an Interconnected Approach of Joint, Mutual and Meta Learning is supported by Modern Operational Research and Experience of the World-Leader Springer Nature! The 5th edition of International Conference on Intelligent Computing and Optimization took place at October 27–28, 2022, via Zoom. Objective was to celebrate “Creativity with Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization across the planet, to share knowledge, experience, innovation—a marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings book of ICO’2022 is published by Springer Nature—Quality Label of wonderful.

Author: Juan Carlos Figueroa-García
Publisher: Springer Nature
ISBN: 3031467396
Category :
Languages : en
Pages : 445

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Author: Obdulia Pichardo Lagunas
Publisher: Springer Nature
ISBN: 3031194934
Category : Computers
Languages : en
Pages : 465

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The two-volume set LNAI 13612 and 13613 constitutes the proceedings of the 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, held in Monterrey, Mexico, in October 2022. The total of 63 papers presented in these two volumes was carefully reviewed and selected from 137 submissions. The first volume, Advances in Computational Intelligence, contains 34 papers structured into three sections: Machine and Deep Learning Image Processing and Pattern Recognition Evolutionary and Metaheuristic Algorithms The second volume contains 29 papers structured into two sections: Natural Language Processing Intelligent Applications and Robotics

Author: Antony Bhavna
Publisher: Springer Nature
ISBN: 3031731190
Category :
Languages : en
Pages : 178

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Author: Henrik I. Christensen
Publisher: Springer Nature
ISBN: 3031441370
Category : Computers
Languages : en
Pages : 466

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This volume LNCS 14253 constitutes the refereed proceedings of the 14th International Conference, ICVS 2023, in Vienna, Austria, in September 2023.. The 37 full papers presented were carefully reviewed and selected from 74 submissions. The conference focuses on Humans and Hands; Medical and Health Care; Farming and Forestry; Automation and Manufacturing; Mobile Robotics and Autonomous Systems; and Performance and Robustness.

Author: Álvaro Herrero
Publisher: Springer Nature
ISBN: 3030578054
Category : Technology & Engineering
Languages : en
Pages : 477

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Book Description
This book contains accepted papers presented at CISIS 2020 held in the beautiful and historic city of Burgos (Spain), in September 2020. The aim of the CISIS 2020 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of computational intelligence, information security, and data mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a thorough peer-review process, the CISIS 2020 International Program Committee selected 43 papers which are published in these conference proceedings achieving an acceptance rate of 28%. Due to the COVID-19 outbreak, the CISIS 2020 edition was blended, combining on-site and on-line participation. In this relevant edition, a special emphasis was put on the organization of five special sessions related to relevant topics as Fake News Detection and Prevention, Mathematical Methods and Models in Cybersecurity, Measurements for a Dynamic Cyber-Risk Assessment, Cybersecurity in a Hybrid Quantum World, Anomaly/Intrusion Detection, and From the least to the least: cryptographic and data analytics solutions to fulfil least minimum privilege and endorse least minimum effort in information systems. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference, and the CISIS conference would not exist without their help.

Author: Martin Werner
Publisher: Springer Nature
ISBN: 3030554627
Category : Computers
Languages : en
Pages : 641

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Book Description
This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.

Author: Maria De Marsico
Publisher: Springer Nature
ISBN: 3031245385
Category : Computers
Languages : en
Pages : 185

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Book Description
This book contains revised and extended versions of selected papers from the 10th and 11th International Conference on Pattern Recognition, ICPRAM 2021 and 2022, held in February 2021 and 2022. Due to COVID-19 pandemic the conferences were held virtually. Both conferences received in total 204 submissions from which 8 full papers were carefully reviewed and selected for presentation in this volume. The papers span a wide range of investigation as well as development lines, which of course always reflect the last trends of research in the pattern recognition community.

Author: Aidan Hogan
Publisher: Morgan & Claypool Publishers
ISBN: 1636392369
Category : Computers
Languages : en
Pages : 257

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Book Description
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.