Pattern Recognition and Classification

IP, Computer Vision, and Pattern Recognition is a compendium of articles and papers that were presented at IPCV '15, an international conference that serves researchers, scholars, professionals, stude

Computer Vision and Pattern Recognition (CVPR) together play an important role in the processes involved in environmental informatics due to their pervasive, non-destructive, effective, and efficient

Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types

This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 201

Information theory has proved to be effective for solving many computer vision & pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feat

Elden (numerical analysis, Linkoping U.) uses as examples handwritten digits, text summarization, pagerank computations made famous by a certain very popular search engine (the name of which is now us

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabr

Target pattern recognition in innate immunity is responsible for the immediate, usually protective, responses shown against invading microorganisms, and it is the principal feature of self and non-sel

Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained

Written by leaders in the field, this book provides a thorough and insightful presentation of the research methodology on emotion recognition in a highly comprehensive writing style. Topics covered in

The main purpose of this book is to resolve deficiencies and limitations that currently exist when using Technical Analysis (TA). Particularly, TA is being used either by academics as an “economic tes

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of

This book is an up-to-date overview on pattern recognition in Computational Molecular Biology, with both a broad coverage of the field and depth at both the fundamental and technical levels. It includ

Mago (IRMACS Centre, Simon Fraser U., Canada) and Bhatia (computer science, DAV College, India) compile 32 articles by a global group of engineering, technology, computer science, math, and other rese

This book presents novel graph-theoretic methods for complex computer vision and pattern recognition tasks. It presents the application of graph theory to low-level processing of digital images, prese

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing

The theories of syntactic pattern recognition and its applications in geophysical intelligent interpretation systems are described in this text for geophysicists, computer scientists, and electrical e

An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved

A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual fo

This book takes the viewpoint that plain symbol processing techniques have little hope of reproducing the depth and breadth of capabilities found in human beings. The book introduces new foundational

As one of the most promising biometric technologies, vein pattern recognition (VPR) is quickly taking root around the world and may soon dominate applications where people focus is key. Among the reas

PATTERN CLASSIFICATIONa unified view of statistical and neural approachesThe product of years of research and practical experience in pattern classification, this book offers a theory-based engineerin

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one

This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical oper

This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the differ

Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields,

Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized, with i