Pattern recognition

This book provides a comprehensive guide to the emerging field of network slicing and its importance to bringing novel 5G applications into fruition.

In this book, the authors discuss the recent developments in computational techniques for automated non-invasive facial emotion detection and analysis with particular focus on the smile.

This is the first book offering a systematic description of tongue image analysis and processing technologies and their typical applications in computerized tongue diagnostic (CTD) systems.

Eye tracking is a widely used research method, but there are many questions and misconceptions about how to effectively apply it.

This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held in Bari, Italy, in October 2016, co-located with the 19th International Conference on Discovery Science, DS 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.

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts.

In the past several years, there have been significant technological advances in the field of crisis response.

The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications.

Smart Homes (SH) offer a promising approach to assisted living for the ageing population.

This book constitutes the refereed post-conference proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018, held in Madrid, Spain, in November 2018The 112 papers presented were carefully reviewed and selected from 187 submissions The program was comprised of 6 oral sessions on the following topics:  machine learning, computer vision, classification, biometrics and medical applications, and brain signals, and also on: text and character analysis, human interaction, and sentiment analysis

Bring magic to your mobile apps using TensorFlow Lite and Core MLKey FeaturesExplore machine learning using classification, analytics, and detection tasks.

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences.

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences.

Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python.

Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery.

This special compendium provides a concise and unified vision of facial image processing.

Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years.

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition.

For the past few years, there has been a growing interest in the study of artificial intelligence and rule-based expert systems.

This book contains a representative cross section of critically reviewed papers from the Third International Symposium on Handwriting and Computer Applications (Montreal, 1987).

Character and handwriting recognition by computers is attracting much attention particularly because of its potential for application in many areas such as office automation, bank check processing, recognition of postal addresses and ZIP Codes, signature verification, and document and text recognition.

From the participation of researchers in most important international conferences in the field, it is noted that activities in automatic document processing have been continuously growing.

In the age of e-society, handwritten signature processing is an enabling technology in a multitude of fields in the "e;digital agenda"e; of many countries, ranging from e-health to e-commerce, from e-government to e-justice, from e-democracy to e-banking, and smart cities.

This volume contains the proceedings of the 7ICIAP held in Monopoli, Italy.

These proceedings present the state of the art in Spanish research on pattern recognition, image processing, speech recognition, and artificial neural networks and applications to medicine, geology, control etc.

The book is an extensive compilation of the papers presented at the IAPR International Workshop on Structural and Syntactic Pattern Recognition SSPR'94.

Handwriting Recognition has become a very important research area which is attracting more and more scientists.

This book is concerned with linear and nonlinear transformations of digitized images and patterns.

This book presents 17 selected papers from the 4th International Graphonomics Society Conference, held at the University of Trondheim (Norway) in July 1989.

This is an up-to-date volume of selected and expanded papers originating from Vision Interface 88, a conference held in Edmonton, Canada.

This volume contains 18 papers of high quality, selected to represent the work that is being developed by Spanish research groups in pattern recognition and image analysis.

The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts.

Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity.

This book contains a selection of 14 papers presented at the workshop organised by the International Association for Pattern Recognition (IAPR) Technical Committee on Syntactical and Structural Pattern Recognition, at Pont-a-Mousson, 1988.

Patterns are becoming the focal point of many areas of scientific endeavour in recent years owing to the progress of computer science, laboratory experiments and observations, and analytical tools.

The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence.

This book is currently the only one on this subject containing both introductory material and advanced recent research results.

This book covers parallel algorithms and architectures and VLSI chips for a range of problems in image processing, computer vision, pattern recognition and artificial intelligence.

Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field.

This book covers the principles and recent research results in intelligent image database systems design.

Traditional methods for image scene interpretation and understanding are based mainly on such single-threaded procedural paradigms as hypothesize-and-test or syntactic parsing.

This book contains 31 selected papers (out of 136 accepted) from the 9th Scandinavian Conference on Image Analysis, held in Uppsala, Sweden, 6-9 June 1995.

This volume deals with the following topics: 2-D, 3-D automata and grammars, parallel architecture for image processing, parallel digital geometry algorithms, data allocation strategies for parallel image processing algorithms, complexity analysis of parallel image operators.

This volume highlights some of the multidisciplinary aspects of automatic signature verification.

Interest in the automatic processing and analysis of document images has been rapidly increasing during the past few years.

This book provides a detailed assessment of the state of the art in automated techniques for the analysis of digital mammogram images.

Thinning is a technique widely used in the pre-processing stage of a pattern recognition system to compress data and to enhance feature extraction in the subsequent stage.