Computer Recognition Systems 2

Computer Recognition Systems 2
Author: Marek Kurzynski
Publisher: Springer Science & Business Media
Total Pages: 1745
Release: 2007-10-15
Genre: Computers
ISBN: 3540751742

Download Computer Recognition Systems 2 Book in PDF, Epub and Kindle

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.

Computational Intelligence and Healthcare Informatics

Computational Intelligence and Healthcare Informatics
Author: Om Prakash Jena
Publisher: John Wiley & Sons
Total Pages: 434
Release: 2021-10-19
Genre: Computers
ISBN: 1119818680

Download Computational Intelligence and Healthcare Informatics Book in PDF, Epub and Kindle

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.

Feature Selection for High-Dimensional Data

Feature Selection for High-Dimensional Data
Author: Verónica Bolón-Canedo
Publisher: Springer
Total Pages: 163
Release: 2015-10-05
Genre: Computers
ISBN: 3319218581

Download Feature Selection for High-Dimensional Data Book in PDF, Epub and Kindle

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.

Proceedings

Proceedings
Author: Tom Fawcett
Publisher:
Total Pages: 0
Release: 2003
Genre: Artificial intelligence
ISBN: 9781577351894

Download Proceedings Book in PDF, Epub and Kindle

Spectral Feature Selection for Data Mining (Open Access)

Spectral Feature Selection for Data Mining (Open Access)
Author: Zheng Alan Zhao
Publisher: CRC Press
Total Pages: 224
Release: 2011-12-14
Genre: Business & Economics
ISBN: 1439862109

Download Spectral Feature Selection for Data Mining (Open Access) Book in PDF, Epub and Kindle

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

Feature Extraction

Feature Extraction
Author: Isabelle Guyon
Publisher: Springer
Total Pages: 765
Release: 2008-11-16
Genre: Computers
ISBN: 3540354883

Download Feature Extraction Book in PDF, Epub and Kindle

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.

Feature Selection for Knowledge Discovery and Data Mining

Feature Selection for Knowledge Discovery and Data Mining
Author: Huan Liu
Publisher: Springer Science & Business Media
Total Pages: 225
Release: 2012-12-06
Genre: Computers
ISBN: 1461556899

Download Feature Selection for Knowledge Discovery and Data Mining Book in PDF, Epub and Kindle

As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Data Driven Approach Towards Disruptive Technologies

Data Driven Approach Towards Disruptive Technologies
Author: T P Singh
Publisher: Springer Nature
Total Pages: 597
Release: 2021-04-06
Genre: Technology & Engineering
ISBN: 9811598738

Download Data Driven Approach Towards Disruptive Technologies Book in PDF, Epub and Kindle

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.

Computational Methods of Feature Selection

Computational Methods of Feature Selection
Author: Huan Liu
Publisher: CRC Press
Total Pages: 437
Release: 2007-10-29
Genre: Business & Economics
ISBN: 1584888792

Download Computational Methods of Feature Selection Book in PDF, Epub and Kindle

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