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Man-Machine Interactions
This volume reflects a number of research streams on the development of computer systems and software that makes it possible to employ them in a variety of human activities ranging from logic studies and artificial intelligence, rule-based control of technological processes, image analysis, expert systems and decision support, to assistance in creative works. In particular, the volume points to a number of new advances in man-machine communication, interaction between visualization and modeling, rough granular computing in human-centric information processing and the discovery of affinities between perceptual granules. The topical subdivisions of this volume include human-computer interactions, decision support, rough fuzzy investigations, advances in classification methodology, pattern analysis and signal processing, computer vision and image analysis, advances in algorithmics, databases and data warehousing, and embedded system applications.
Man-Machine Interactions 2
Man-machine interaction is the interdisciplinary field, focused on a human and a machine in conjunction. It is the intersection of computer science, behavioural sciences, social psychology, ergonomics, security. It encompasses study, design, implementation, and evaluation of small- and large-scale, interacting, computing, hardware and software systems dedicated for human use. Man-machine interaction builds on supportive knowledge from both sides, the machine side providing techniques, methods and technologies relevant for computer graphics, visualisation, programming environments, the human side bringing elements of communication theory, linguistics, social sciences, models of behaviour. The...
Advances in Feature Selection for Data and Pattern Recognition
This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.
Data Science Concepts and Techniques with Applications
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared ...
Advanced Machine Learning Technologies and Applications
This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012. The 58 full papers presented were carefully reviewed and selected from 99 intial submissions. The papers are organized in topical sections on rough sets and applications, machine learning in pattern recognition and image processing, machine learning in multimedia computing, bioinformatics and cheminformatics, data classification and clustering, cloud computing and recommender systems.
Hybrid Artificial Intelligent Systems
The two LNAI volumes 6678 and 6679 constitute the proceedings of the 6th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2011, held in Wroclaw, Poland, in May 2011. The 114 papers published in these proceedings were carefully reviewed and selected from 241 submissions. They are organized in topical sessions on hybrid intelligence systems on logistics and intelligent optimization; metaheuristics for combinatorial optimization and modelling complex systems; hybrid systems for context-based information fusion; methods of classifier fusion; intelligent systems for data mining and applications; systems, man, and cybernetics; hybrid artificial intelligence systems in management of production systems; hybrid artificial intelligent systems for medical applications; and hybrid intelligent approaches in cooperative multi-robot systems.
Hybrid Artificial Intelligent Systems
This book constitutes the refereed proceedings of the 16th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2021, held in Bilbao, Spain, in September 2021. The 44 full and 11 short papers presented in this book were carefully reviewed and selected from 81 submissions. The papers are grouped into these topics: data mining, knowledge discovery and big data; bio-inspired models and evolutionary computation; learning algorithms; visual analysis and advanced data processing techniques; machine learning applications; hybrid intelligent applications; deep learning applications; and optimization problem applications.
Intelligent Systems in Industrial Applications
This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.
Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam
This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being. This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches. We are proud to offer the readers this book.
Intelligent Decision Technologies 2017
The volume presents a collection of peer-reviewed articles from the 9th KES International Conference on Intelligent Decision Technologies (KES-IDT-17), held in Vilamoura, Algarve, Portugal on 21–23 June 2017. The conference addressed critical areas of computer science, as well as promoting knowledge transfer and the generation of new ideas in the field of intelligent decision making, project management and data analysis. The range of topics addressed includes methods of classification, prediction, data analysis, decision support, modeling, social media and many more in such diverse areas as finance, linguistics, management and transportation.
