Download or read book Computer Recognition Systems 2 written by Marek Kurzynski and published by Springer Science & Business Media. This book was released on 2007-10-15 with total page 1745 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the results of the 5th International Conference on Computer Recognition Systems CORES’07 held 22-25 October 2007 in Hotel Tumski, Wroclaw, Poland. It brings together original research results in both methodological issues and different application areas of pattern recognition. The contributions cover all topics in pattern recognition including, for example, classification and interpretation of text, video, and voice.
Download or read book Proceedings written by Tom Fawcett and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Intelligence and Healthcare Informatics written by Om Prakash Jena and published by John Wiley & Sons. This book was released on 2021-10-19 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: COMPUTATIONAL INTELLIGENCE and HEALTHCARE INFORMATICS The book provides the state-of-the-art innovation, research, design, and implements methodological and algorithmic solutions to data processing problems, designing and analysing evolving trends in health informatics, intelligent disease prediction, and computer-aided diagnosis. Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. With the rapid advance of technology, artificial intelligence (AI) techniques are being effectively used in the fields of health to improve the efficiency of treatments, avoid the risk of false diagnoses, make therapeutic decisions, and predict the outcome in many clinical scenarios. Modern health treatments are faced with the challenge of acquiring, analyzing and applying the large amount of knowledge necessary to solve complex problems. Computational intelligence in healthcare mainly uses computer techniques to perform clinical diagnoses and suggest treatments. In the present scenario of computing, CI tools present adaptive mechanisms that permit the understanding of data in difficult and changing environments. The desired results of CI technologies profit medical fields by assembling patients with the same types of diseases or fitness problems so that healthcare facilities can provide effectual treatments. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with it. Contained in this book are state-of-the-art methods of computational intelligence and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide researchers with a platform encompassing state-of-the-art innovations; research and design; implementation of methodological and algorithmic solutions to data processing problems; and the design and analysis of evolving trends in health informatics, intelligent disease prediction and computer-aided diagnosis. Audience The book is of interest to artificial intelligence and biomedical scientists, researchers, engineers and students in various settings such as pharmaceutical & biotechnology companies, virtual assistants developing companies, medical imaging & diagnostics centers, wearable device designers, healthcare assistance robot manufacturers, precision medicine testers, hospital management, and researchers working in healthcare system.
Download or read book Feature Selection for High Dimensional Data written by Verónica Bolón-Canedo and published by Springer. This book was released on 2015-10-05 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers. The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
Download or read book Spectral Feature Selection for Data Mining written by Zheng Alan Zhao and published by CRC Press. This book was released on 2011-12-14 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise
Download or read book Computational Methods of Feature Selection written by Huan Liu and published by CRC Press. This book was released on 2007-10-29 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Download or read book Feature Extraction written by Isabelle Guyon and published by Springer. This book was released on 2008-11-16 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.
Download or read book Data Driven Approach Towards Disruptive Technologies written by T P Singh and published by Springer Nature. This book was released on 2021-04-06 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4–5 September 2020. The book addresses the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like data-driven industrial IoT, bioinformatics, network and security, autonomous computing and various other aligned areas. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber-physical system and smart agriculture. All papers have been carefully reviewed. The book is of interest to computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
Download or read book Innovations in Computer Science and Engineering written by H. S. Saini and published by Springer. This book was released on 2019-06-18 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality, peer-reviewed research papers from the 6thInternational Conference on Innovations in Computer Science & Engineering (ICICSE 2018), held at Guru Nanak Institutions, Hyderabad, India from August 17 to 18, 2018. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques and offers a platform for researchers from academia and industry to present their original work and exchange ideas, information, techniques and applications in the field of computer science.
Download or read book Introduction to Machine Learning with Python written by Andreas C. Müller and published by "O'Reilly Media, Inc.". This book was released on 2016-09-26 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
Download or read book Artificial Intelligence written by Bart Verheij and published by Springer. This book was released on 2018-02-24 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of the best papers of the 29th Benelux Conference on Artificial Intelligence, BNAIC 2017, held in Groningen, The Netherlands, in November 2017. The 11 full papers presented in this volume were carefully reviewed and selected from 30 submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
Download or read book Machine Intelligence in Design Automation written by Rohit Sharma and published by . This book was released on 2018-03-13 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a hands-on approach for solving electronic design automation problems with modern machine intelligence techniques by including step-by-step development of commercial grade design applications including resistance estimation, capacitance estimation, cell classification and others using dataset extracted from designs at 20nm. It walks the reader step by step in building solution flow for EDA problems with Python and Tensorflow.Intended audience includes design automation engineers, managers, executives, research professionals, graduate students, Machine learning enthusiasts, EDA and CAD developers, mentors, and the merely inquisitive. It is organized to serve as a compendium to a beginner, a ready reference to intermediate and source for an expert.
Download or read book High dimensional Data Analysis written by Tony Cai;Xiaotong Shen and published by . This book was released on with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few years, significant developments have been taking place in highdimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. In particular, substantial advances have been made in the areas of feature selection, covariance estimation, classification and regression. This book intends to examine important issues arising from highdimensional data analysis to explore key ideas for statistical inference and prediction. It is structured around topics on multiple hypothesis testing, feature selection, regression, cla.
Download or read book Evolutionary Machine Learning Techniques written by Seyedali Mirjalili and published by Springer Nature. This book was released on 2019-11-11 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavi
Download or read book Applications in Ubiquitous Computing written by Raman Kumar and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a deep dive into ubiquitous computing for applications in health, business, education, tourism, and transportation. The rich interdisciplinary contents of the book appeal to readers from diverse disciplines who aspire to create new and innovative research initiatives and applications in ubiquitous computing. Topics include condition monitoring and diagnostics; multi-objective optimization in design, multi-objective optimization of machining parameters, and more. The book benefits researchers, advanced students, as well as practitioners interested in applications of ubiquitous computing. Features practical, tested applications in ubiquitous computing Includes applications such as health, business, education, electronics, tourism, and transportation Applicable to researchers, academics, students, and professionals.
Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
