Learn IT - Books tags algorithms

Emerging Spatial Information Systems and Applications

IGI Global, 2006

Spatial information systems were created manually for many years. For example, historically, the source of cholera in London in 1854 was found by John Snow, by mapping where victims of the disease lived. The graph clearly showed them to be close to the Broad Street Pump,1 one of the city’s water wells. Another example is Zipf’s Law,2...

Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems

Springer, 2006

This book presents a unique combination of mobile robots and embedded systems, from introductory to intermediate level. It is structured in three parts, dealing with embedded systems (hardware and software design, actuators, sensors, PID control, multitasking), mobile robot design (driving, balancing, walking, and flying robots), and mobile...

3D Face Processing: Modeling, Analysis and Synthesis (The International Series in Video Computing)

Springer, 2004

3D Face Processing: Modeling, Analysis and Synthesis introduces the frontiers of 3D face processing techniques. It reviews existing 3D face processing techniques, including techniques for 3D face geometry modeling; 3D face motion modeling; and 3D face motion tracking and animation. Then it discusses a unified framework for face...

Digital Image Processing

Springer, 1997

The sixth edition of this worldwide used textbook was thoroughly revised and extended. Throughout the whole text you will find numerous improvements, extensions, and updates. Above all, I would like to draw your attention to two major changes.

Firstly, the whole textbook is now clearly partitioned into basic and advanced material in...

Robust Statistics: Theory and Methods (Probability and Statistics)

John Wiley & Sons, 2006

Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and...

Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)

Springer, 2005

The support vector machine (SVM) is a supervised learning method that generates input-output mapping functions from a set of labeled training data. The mapping function can be either a classification function, i.e., the category of the input data, or a regression function. For classification, nonlinear kernel functions are often used to...

Mining Graph Data

John Wiley & Sons, 2006

Data mining, or knowledge discovery in databases, is a large area of study and is populated with numerous theoretical and practical textbooks. In this book, we take a focused and comprehensive look at one topic within this field: mining data that is represented as a graph. We attempt to cover the full breadth of the topic, including graph...

Geographic Information Metadata for Spatial Data Infrastructures: Resources, Interoperability and Information Retrieval

Springer, 2005

Metadata play a fundamental role in both DLs and SDIs. Commonly defined as "structured data about data" or "data which describe attributes of a resource" or, more simply, "information about data", it is an essential requirement for locating and evaluating available data. Therefore, this book focuses on the study of...

Designing with Blends: Conceptual Foundations of Human-Computer Interaction and Software Engineering

MIT Press, 2007

The evolution of the concept of mind in cognitive science over the past 25 years creates new ways to think about the interaction of people and computers. New ideas about embodiment, metaphor as a fundamental cognitive process, and conceptual integration--a blending of older concepts that gives rise to new, emergent properties--have become...

Foundations of Learning Classifier Systems (Studies in Fuzziness and Soft Computing)

Springer, 2005

Learning Classifier Systems (LCS) [Holland, 1976] are a machine learning technique which combines evolutionary computing, reinforcement learning, supervised learning or unsupervised learning, and heuristics to produce adaptive systems. They are rulebased systems, where the rules are usually in the traditional production system form of “IF...

Adaptive Business Intelligence

Springer, 2006

From the reviews of the first edition:

"In this book the authors explain the science and application of numerous prediction and optimization techniques as well as how these concepts can be used to develop adaptive decision-making systems. The book is suitable for business and IT managers who make decisions in complex industrial and...

Statistical Mechanics of Learning

Cambridge University Press, 2001

The effort to build machines that are able to learn and undertake tasks such as datamining, image processing and pattern recognition has led to the development of artificial neural networks in which learning from examples may be described and understood. The contribution to this subject made over the past decade by researchers applying the...

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