This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks. Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter notebooks, which can be downloaded from the book website.

An approach to defining the conceptual bases of pattern recognition in mathematics, through the development of appropriate models based largely on homotopy theory and generalized shape theory. Topics include the problem of pattern recognition, topological and structural framework, and the formalization of recognition by means of a categorical framework. Appropriate as a graduate textbook on the mathematics of pattern recognition. Annotation(c) 2003 Book News, Inc., Portland, OR (booknews.com)

For many years researchers in the field of Handwriting Recognition were considered to be working in an area of minor importance in Pattern Recog nition. They had only the possibility to present the results of their research at general conferences such as the ICPR or publish their papers in journals such as some of the IEEE series or PR, together with many other papers generally oriented to the more promising areas of Pattern Recognition. The series of International Workshops on Frontiers in Handwriting Recog nition and International Conferences on Document Analysis and Recognition together with some special issues of several journals are now fulfilling the expectations of many researchers who have been attracted to this area and are involving many academic institutions and industrial companies. But in order to facilitate the introduction of young researchers into the field and give them both theoretically and practically powerful tools, it is now time that some high level teaching schools in handwriting recognition be held, also in order to unite the foundations of the field. Therefore it was my pleasure to organize the NATO Advanced Study Institute on Fundamentals in Handwriting Recognition that had its origin in many exchanges among the most important specialists in the field, during the International Workshops on Frontiers in Handwriting Recognition.

Is it possible to learn something without being aware of it? How does emotion influence the way we think? How can we improve our memory? Fundamentals of Cognition, third edition, provides a basic, reader-friendly introduction to the key cognitive processes we use to interact successfully with the world around us. Our abilities in attention, perception, learning, memory, language, problem solving, thinking, and reasoning are all vitally important in enabling us to cope with everyday life. Understanding these processes through the study of cognitive psychology is essential for understanding human behaviour. This edition has been thoroughly updated and revised with an emphasis on making it even more accessible to introductory-level students. Bringing on board Professor Marc Brysbaert, a world-leading researcher in the psychology of language, as co-author, this new edition includes: developed and extended research activities and "In the Real World" case studies to make it easy for students to engage with the material; new real-world topics such as discussions of attention-deficit/hyperactivity disorder, the reading problems of individuals with dyslexia, why magic tricks work, and why we cannot remember the Apple logo accurately; a supporting companion website containing multiple choice questions, flashcards, sample essay answers, instructor resources, and more. The book provides a perfect balance between traditional approaches to cognition and cutting-edge cognitive neuroscience and cognitive neuropsychology. Covering all the key topics within cognition, this comprehensive overview is essential reading for all students of cognitive psychology and related areas such as clinical psychology.

This book is a detailed description of the basics of three-dimensional digital image processing. A 3D digital image (abbreviated as “3D image” below) is a digitalized representation of a 3D object or an entire 3D space, stored in a computer as a 3D array. Whereas normal digital image processing is concerned with screens that are a collection of square shapes called “pixels” and their corresponding density levels, the “image plane” in three dimensions is represented by a division into cubical graphical elements (called “voxels”) that represent corresponding density levels. Inthecontextofimageprocessing,in manycases3Dimageprocessingwill refer to the input of multiple 2D images and performing processing in order to understand the 3D space (or “scene”) that they depict. This is a result of research into how to use input from image sensors such as television cameras as a basis for learning about a 3D scene, thereby replicating the sense of vision for humans or intelligent robots, and this has been the central problem in image processing research since the 1970s. However, a completely di?erent type of image with its own new problems, the 3D digital image discussed in this book, rapidly took prominence in the 1980s, particularly in the ?eld of medical imaging. These were recordings of human bodies obtained through computed (or “computerized”) tomography (CT),imagesthatrecordednotonlytheexternal,visiblesurfaceofthesubject but also, to some degree of resolution, its internal structure. This was a type of image that no one had experienced before.

This book contains keynote lectures and full papers presented at the International Symposium on Computational Modelling of Objects Represented in Images (CompIMAGE), held in Coimbra, Portugal, on 20-21 October 2006. International contributions from nineteen countries provide a comprehensive coverage of the current state-of-the-art in the fields of: - Image Processing and Analysis; - Image Segmentation; - Data Interpolation; - Registration, Acquisition and Compression; - 3D Reconstruction; - Objects Tracking; - Motion and Deformation Analysis; - Objects Simulation; - Medical Imaging; - Computational Bioimaging and Visualization. Related techniques also covered in this book include the finite element method, modal analyses, stochastic methods, principal and independent components analyses and distribution models. Computational Modelling of Objects Represented in Images will be useful to academics, researchers and professionals in Computational Vision (image processing and analysis), Computer Sciences, and Computational Mechanics.

This volume is dedicated to the 15th Symposium on Fundamentals of Computation Theory FCT 2005, held in Lubeck, Germany, on August 17–20, 2005.