Image Processing and Pattern Recognition

• Author : Cornelius T. Leondes
• Publisher : Elsevier
• Release : 09 February 1998

Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those working at financial institutions, will value this unique and authoritative reference to diverse applications methodologies. Coverage includes: Optical character recognition Speech classification

• Author : M. Narasimha Murty,V. Susheela Devi
• Publisher : Springer Science & Business Media
• Release : 25 May 2011

Observing the environment and recognising patterns for the purpose of decision making is fundamental to human nature. This book deals with the scientific discipline that enables similar perception in machines through pattern recognition (PR), which has application in diverse technology areas. This book is an exposition of principal topics in PR using an algorithmic approach. It provides a thorough introduction to the concepts of PR and a systematic account of the major topics in PR besides reviewing the vast progress

• Author : K. S. Fu
• Publisher : Springer Science & Business Media
• Release : 08 March 2013

During the past fifteen years there has been a considerable growth of interest in problems of pattern recognition. Contributions to the blossom of this area have come from many disciplines, including statistics, psychology, linguistics, computer science, biology, taxonomy, switching theory, communication theory, control theory, and operations research. Many different approaches have been proposed and a number of books have been published. Most books published so far deal with the decision-theoretic (or statistical) approach or the syntactic (or linguistic) approach. Since

• Author : Jürgen Beyerer,Matthias Richter,Matthias Nagel
• Publisher : Walter de Gruyter GmbH & Co KG
• Release : 04 December 2017

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book is to clarifies the concepts so that

• Author : José Francisco Martínez-Trinidad,Jesús Ariel Carrasco-Ochoa,José Arturo Olvera-López,Sudeep Sarkar
• Publisher : Springer
• Release : 20 June 2018

This book constitutes the proceedings of the 10th Mexican Conference on Pattern Recognition, MCPR 2018, held in Puebla, Mexico, in June 2018. The 28 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in topical sections named: pattern recognition principles; deep learning, neural networks and associative memories; data mining; and computer vision.

• Author : Jesús Ariel Carrasco-Ochoa,José Francisco Martínez-Trinidad,José Arturo Olvera-López
• Publisher : Springer
• Release : 31 May 2017

This book constitutes the refereed proceedings of the 9th Mexican Conference on Pattern Recognition, MCPR 2017, held in Huatulco, Mexico, in June 2017. The 29 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on pattern recognition and artificial intelligence techniques, image processing and analysis, robotics and remote sensing, natural language processing and recognition, applications of pattern recognition.

• Author : Albert Nigrin
• Publisher : MIT Press
• Release : 11 August 1993

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern

• Author : Joachim Denzler,Gunther Notni,Herbert Süße
• Publisher : Springer Science & Business Media
• Release : 03 September 2009

In 2009, for the second time in a row, Jena hosted an extraordinary event. In th 2008, Jena celebrated the 450 birthday of the Friedrich Schiller University of Jena with the motto “Lichtgedanken” – “?ashes of brilliance. ” This year, for almost one week, Jena became the center for the pattern recognition research st community of the German-speaking countries in Europe by hosting the 31 Annual Symposium of the Deutsche Arbeitsgemeinschaft fur ¨ Mustererkennung (DAGM). Jena is a special place for this event for several reasons. Firstly,

• Author : H Bunke,A Sanfeliu
• Publisher : World Scientific
• Release : 01 January 1990

This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition. The book consists of individual chapters written

• Author : Horst Bunke,Abraham Kandel
• Publisher : World Scientific
• Release : 11 August 2022

The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data

• Author : Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner
• Publisher : Springer
• Release : 03 October 2005

This LNCS volume contains the papers presented at the 3rd International Conference on Advances in Pattern Recognition (ICAPR 2005) organized in August, 2005 in the beautiful city of Bath, UK.

• Author : Sameer Singh,Nabeel Murshed,Walter Kropatsch
• Publisher : Springer
• Release : 29 June 2003

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation

• Author : Huimin Ma,Liang Wang,Changshui Zhang,Fei Wu,Tieniu Tan,Yaonan Wang,Jianhuang Lai,Yao Zhao
• Publisher : Springer Nature
• Release : 22 October 2021

The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and

• Author : Antonio Robles-Kelly,Marco Loog,Battista Biggio,Francisco Escolano,Richard Wilson
• Publisher : Springer
• Release : 04 November 2016

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The 51 full papers presented were carefully reviewed and selected from 68 submissions. They are organized in the following topical sections: dimensionality reduction, manifold learning and embedding methods; dissimilarity representations; graph-theoretic methods; model selection, classification and clustering; semi and

• Author : K. C. Santosh,Ravindra S. Hegadi
• Publisher : Springer
• Release : 15 July 2019

This three-book set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis;