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Probability and Statistics for Computer Scientists
Probability and Statistics for Computer Scientists

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools
Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic
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Kernel Smoothing: Principles, Methods and Applications
Kernel Smoothing: Principles, Methods and Applications

Comprehensive theoretical overview of kernel smoothing methods with motivating examples

Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of...

Digital Signal Processing: An Introduction with MATLAB and Applications
Digital Signal Processing: An Introduction with MATLAB and Applications

In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis....

Data Mining for Bioinformatics
Data Mining for Bioinformatics

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining...

Mobile Robot Navigation with Intelligent Infrared Image Interpretation
Mobile Robot Navigation with Intelligent Infrared Image Interpretation

Mobile robots require the ability to make decisions such as "go through the hedges" or "go around the brick wall." Mobile Robot Navigation with Intelligent Infrared Image Interpretation describes in detail an alternative to GPS navigation: a physics-based adaptive Bayesian pattern classification model that uses a...

Optimisation in Signal and Image Processing
Optimisation in Signal and Image Processing

This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic...

3D Computer Vision: Efficient Methods and Applications (X.media.publishing)
3D Computer Vision: Efficient Methods and Applications (X.media.publishing)

This book provides an introduction to the foundations of three-dimensional computer vision and describes recent contributions to the field. Geometric methods include linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and...

Inverse Problem Theory and Methods for Model Parameter Estimation
Inverse Problem Theory and Methods for Model Parameter Estimation
‘Tarantola's book is undoubtedly the most important work on probabilistic inverse theory. It presents a complete theory where a physical parameter is represented, not by a number, but by a probability distribution.’ Klaus Mosegaard, Niels Bohr Institute

The use of actual observations to infer the properties of a
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Mathematical Statistics for Economics and Business
Mathematical Statistics for Economics and Business

Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics.  The selection of topics in this textbook is designed to provide students with a...

Spatial AutoRegression (SAR) Model: Parameter Estimation Techniques (SpringerBriefs in Computer Science)
Spatial AutoRegression (SAR) Model: Parameter Estimation Techniques (SpringerBriefs in Computer Science)
Explosive growth in the size of spatial databases has highlighted the need for spatial data analysis and spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. Extracting useful and interesting patterns from massive geo-spatial datasets is important for many application...
The Scrum Field Guide: Agile Advice for Your First Year and Beyond (2nd Edition)
The Scrum Field Guide: Agile Advice for Your First Year and Beyond (2nd Edition)

Extensively revised to reflect improved Scrum practices and tools, this edition adds an all-new section of tips from the field. 



The 1st Edition has a 5-Star Amazon Customer Rating and 135 reviews.

Thousands of organizations are adopting Scrum to
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Depth Map and 3D Imaging Applications: Algorithms and Technologies
Depth Map and 3D Imaging Applications: Algorithms and Technologies
This book has three editors, and all of us are involved in image processing and computer vision research. We have contributed to the 3D imaging research, especially in the field of passive optical 3D shape recovery methods. Over the last decade, significant progress had been made in 3D imaging research. As a result, 3D imaging...
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