Object Recognition

Object Recognition

This volume introduces the fundamental concepts and tools involved in the design and implementation of object recognition systems. Divided into three parts, it first introduces the topic and covers the acquisition of images, then details 3-D object reconstruction, modelling and matching, and finally describes typical recognition systems using case studies. Key features include: Extensive literature surveys of state-of-the-art systems Recognition will be essential reading for research scientists, advanced undergraduate and postgraduate students in computer vision, image processing and pattern classification. It will also be of interest to practitioners working in the field of computer vision.

Object Recognition

Soft Computing Approach to Pattern Classification and Object Recognition

Soft Computing Approach to Pattern Classification and Object Recognition

Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition. The book also surveys various soft computing tools, fuzzy relational calculus (FRC), genetic algorithm (GA) and multilayer perceptron (MLP) to provide a strong foundation for the reader. The supervised approach to pattern classification and model-based approach to occluded object recognition are treated in one framework , one based on either a conventional interpretation or a new interpretation of multidimensional fuzzy implication (MFI) and a novel notion of fuzzy pattern vector (FPV). By combining practice and theory, a completely independent design methodology was developed in conjunction with this supervised approach on a unified framework, and then tested thoroughly against both synthetic and real-life data. In the field of soft computing, such an application-oriented design study is unique in nature. The monograph essentially mimics the cognitive process of human decision making, and carries a message of perceptual integrity in representational diversity. Soft Computing Approach to Pattern Classification and Object Recognition is intended for researchers in the area of pattern classification and computer vision. Other academics and practitioners will also find the book valuable.

Soft Computing Approach to Pattern Classification and Object Recognition

Correctional Counseling and Rehabilitation - Eighth Edition

Correctional Counseling and Rehabilitation - Eighth Edition

This text presents foundations of correctional intervention, including overviews of the major systems of therapeutic intervention, diagnosis of mental illness, and correctional assessment and classification. Its detailed descriptions and cross-approach comparisons can help professionals better determine which of several techniques might be especially useful in their particular setting.

Correctional Counseling and Rehabilitation - Eighth Edition

Equivariant Degree Theory

Equivariant Degree Theory

This book presents a new degree theory for maps which commute with a group of symmetries. This degree is no longer a single integer but an element of the group of equivariant homotopy classes of maps between two spheres and depends on the orbit types of the spaces. The authors develop completely the theory and applications of this degree in a self-contained presentation starting with only elementary facts. The first chapter explains the basic tools of representation theory, homotopy theory and differential equations needed in the text. Then the degree is defined and its main abstract properties are derived. The next part is devoted to the study of equivariant homotopy groups of spheres and to the classification of equivariant maps in the case of abelian actions. These groups are explicitely computed and the effects of symmetry breaking, products and composition are thorougly studied. The last part deals with computations of the equivariant index of an isolated orbit and of an isolated loop of stationary points. Here differential equations in a variety of situations are considered: symmetry breaking, forcing, period doubling, twisted orbits, first integrals, gradients etc. Periodic solutions of Hamiltonian systems, in particular spring-pendulum systems, are studied as well as Hopf bifurcation for all these situations.

Equivariant Degree Theory

Foundations of Hyperbolic Manifolds - Second Edition

Foundations of Hyperbolic Manifolds - Second Edition

This book is an exposition of the theoretical foundations of hyperbolic manifolds. It is intended to be used both as a textbook and as a reference. The reader is assumed to have a basic knowledge of algebra and topology at the first year graduate level of an American university. The book is divided into three parts. The first part is concerned with hyperbolic geometry and discrete groups. The second part is devoted to the theory of hyperbolic manifolds. The third part integrates the first two parts in a development of the theory of hyperbolic orbifolds. The second edition contains hundreds of changes and corrections, and new additions include: A more thorough discussion of polytopes; Discussion of Simplex Reflection groups has been expanded to give a complete classification of the Gram matrices of spherical, Euclidean and hyperbolic n-simplices; A new section on the volume of a simplex, in which a derivation of Schlaflis differential formula is presented; A new section with a proof of the n-dimensional Gauss-Bonnet theorem. The exercises have been thoroughly reworked, pruned, and upgraded, and over 100 new exercises have been added. The author has also prepared a solutions manual which is available to professors who choose to adopt this text for their course.

Foundations of Hyperbolic Manifolds - Second Edition

Platypus

Platypus

This is the enigmatic story of a biological riddle that confounded scientists for nearly ninety years, challenging theories of creationism, evolution, and classification of species along the way. Secretive, elusive, and beguiling, the platypus has continued to captivate public and scientific attention to the present day.

Platypus

Machine Learning in Action

Machine Learning in Action

A machine is said to learn when its , improves with experience. Learning requires algorithms and programs that capture data and ferret out the interesting or useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many.,

Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you’ll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data , in code you can reuse. You’ll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification.

Machine Learning in Action

Python 3 Text Processing with NLTK 3 Cookbook

Python 3 Text Processing with NLTK 3 Cookbook

This book will show you the essential techniques of text and language processing. Starting with tokenization, stemming, and the WordNet dictionary, you’ll progress to part-of-speech tagging, phrase chunking, and named entity recognition. You’ll learn how various text corpora are organized, as well as how to create your own custom corpus. Then, you’ll move onto text classification with a focus on sentiment analysis. And because NLP can be computationally expensive on large bodies of text, you’ll try a few methods for distributed text processing. Finally, you’ll be introduced to a number of other small but complementary Python libraries for text analysis, cleaning, and parsing.

Python 3 Text Processing with NLTK 3 Cookbook