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This volume constitutes the proceedings of the 10th International Conference on Artificial Intelligence and Soft Computing, ICAISC'2010, held in Zakopane, Poland in June 13-17, 2010. The articles are organized in topical sections on Fuzzy Systems and Their Applications; Data Mining, Classification and Forecasting; Image and Speech Analysis; Bioinformatics and Medical Applications (Volume 6113) together with Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; Agent System, Robotics and Control; Various Problems aof Artificial Intelligence (Volume 6114).
This book presents the proceedings of the 1st International Symposium on Intelligent and Distributed Computing, IDC 2007, held in Craiova, Romania, October 2007. Coverage includes: autonomous and adaptive computing; data mining and knowledge discovery; distributed problem solving and decision making; e-business, e-health and e-learning; genetic algorithms; image processing; information retrieval; intelligence in mobile and ubiquitous computing.
The two-volume set LNAI 7894 and LNCS 7895 constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2013, held in Zakopane, Poland in June 2013. The 112 revised full papers presented together with one invited paper were carefully reviewed and selected from 274 submissions. The 56 papers included in the second volume are organized in the following topical sections: evolutionary algorithms and their applications; data mining; bioinformatics and medical applications; agent systems, robotics and control; artificial intelligence in modeling and simulation; and various problems of artificial intelligence.
In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009) and “Intelligent Computer Graphics 2010” (2010). This volume contains selected extended papers from the last 3IA Conference (3IA’2011), which has been held in Athens (Greece) in May 2011. This year papers are particularly exciting and concern areas like virtual reality, artificial life, data visualization, games, global illumination, point cloud modelling, declarative modelling, scene reconstruction and many other very important themes.
This collection aims to explore the transformative potential of computer vision and artificial intelligence (AI) in revolutionizing medical imaging. Medical imaging is still in a state of infancy. The interpretation of medical images is often time-consuming and subject to human error. By leveraging computer vision algorithms and AI technologies, medical imaging can be enhanced with automated analysis, pattern recognition, and predictive modelling, leading to improved accuracy, speed, and clinical outcomes. This collection provides an overview of the current state, challenges, and prospects of integrating computer vision and AI techniques into existing medical imaging technologies. Medical imaging has the potential to create a paradigm shift in healthcare in future enhancing diagnostic accuracy, personalised treatment, and overall patient care. While challenges related to data quality, interpretability, and ethics must be navigated, the future for AI based imaging technology is bright.
Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of machine learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement machine learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of machine learning quickly.
The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.
The present book includes a set of selected extended papers from the first International Joint Conference on Computational Intelligence (IJCCI 2009), held in Madeira, Portugal, from 5 to 7 October 2009. The conference was composed by three co-located conferences: The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 231 submissions, from 35 countries, in all continents. After a double blind paper review performed by the Program Committee, ...
Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.
Ten years of ,,Fuzzy Days“ in Dortmund! What started as a relatively small workshop in 1991 has now become one of the best known smaller conferences on Computational Intelligence in the world. It fact, it was (to my best knowledge) the ?rst conference to use this term, in 1994, although I confess that another, larger conference was announced ?rst and the trade mark “Computational Intelligence was not coined in Dortmund. I believe, that the success of this conference is grounded on the quality of its reviewedandinvitedpapersaswellasitsgoodorganization. Fromthebeginning, we have sent every paper anonymously to ?ve referees, and we have always accepted only around 50% of the papers sent in....