Readership: Engineers and computer scientists.
keywords:Active Vision;Robot Vision;Computer Vision;Model-Based Vision;Robot Navigation;Reactive Control;Robot Motion Planning;Knowledge-Based Vision;Robotics
Readership: Computer scientists.
keywords:Machine Learning and Vision;Visualization;Geograpgic Information Systems;Object Recognition;Surveillance;Multimedia;Image Understanding
Contents: Methodology:Simultaneous Feature Analysis and System Identification in a Neuro-Fuzzy Framework (N R Pal & D Chakraborty)Neuro-Fuzzy Model for Unsupervised Feature Extraction with Real Life Applications (R K De et al.)A Computational-Intelligence-Based Approach to Decision Support (M B Gorzalczany)Clustering Problem Using Fuzzy C-Means Algorithms and Unsupervised Neural Networks (J-S Lin)Automatic Training of Min-Max Classifiers (A Rizzi)Granular Computing in Pattern Recognition (W Pedrycz & G Vukovich)ART-Based Model Set for Pattern Recognition: FasArt Family (G I Sainz Palmero et al.)Applications:A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolving Fuzzy Neural Networks (N Kasabov & G Iliev)Neural Versus Heuristic Development of Choquet Fuzzy Integral Fusion Algorithms for Land Mine Detection (P D Gader et al.)Automatic Segmentation of Multi-Spectral MR Brain Images Using a Neuro-Fuzzy Algorithm (S Y Lee et al.)Vision-Based Neuro-Fuzzy Control of Autonomous Lane Following Vehicle (Y-J Ryoo)
Readership: Graduate students, lecturers and researchers in computer science and computer engineering.
Keywords:Neuro-Fuzzy;Fuzzy Logic;Neural Networks;Pattern Recognition;Classification;Clustering;Decision Making;Uncertainty Management
Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and others. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.Contents:Neuro-Fuzzy Systems:Fuzzification of Neural Networks for Classification Problems (H Ishibuchi & M Nii)Neural Networks for Structural Pattern Recognition:Adaptive Graphic Pattern Recognition: Foundations and Perspectives (G Adorni et al.)Adaptive Self-Organizing Map in the Graph Domain (S Günter & H Bunke)Clustering for Hybrid Systems:From Numbers to Information Granules: A Study in Unsupervised Learning and Feature Analysis (A Bargiela & W Pedrycz)Combining Neural Networks and Hidden Markov Models:Combination of Hidden Markov Models and Neural Networks for Hybrid Statistical Pattern Recognition (G Rigoll)From Character to Sentences: A Hybrid Neuro-Markovian System for On-Line Handwriting Recognition (T Artières et al.)Multiple Classifier Systems:Multiple Classifier Combination: Lessons and Next Steps (T K Ho)Design of Multiple Classifier Systems (F Roli & G Giacinto)Fusing Neural Networks Through Fuzzy Integration (A Verikas et al.)Applications of Hybrid Systems:Hybrid Data Mining Methods in Image Processing (A Klose & R Kruse)Robust Fingerprint Identification Based on Hybrid Pattern Recognition Methods (D-W Jung & R-H Park)Text Categorization Using Learned Document Features (M Junker et al.)
Readership: Graduate students, lecturers and researchers in computer science, computer engineering, electrical engineering and related fields.
Keywords:Neural Network;Fuzzy Systems;Soft Computing;Hidden Markov Model;Data Mining;Machine Learning;Pattern Recognition;Clustering;Granular Computing;Multiple Classifier System;Neural Network Fusion;Image Processing;Fingerprint Identification;Handwriting Recognition
Readership: Researchers in computer science, robotics, applied mathematics & engineering and electronics.
keywords:Path Planning;Motion Planning;Navigation;Localization;Pose Tracking;Vision;Shape Recognition;Object Recognition;Distributed Systems;Multiple Robot Interaction;Human Robot Interaction;Telerobotics
Contents:Range Estimation from Camera Blur by Regularized Adaptive Identification (L F Holeva)Modeling Sensor Confidence for Sensor Integration Tasks (K Hughes & N Ranganathan)From 3-D Scattered Data to Geometric Signal Description: Invariant Stable Recovery of Straight Line Segments (P Hébert et al.)Feature Extraction and Matching as Signal Detection (X-P Hu & N Ahuja)Non-Parametric Multiscale Curve Smoothing (P L Rosin)Integration of Geometric and Non-Geometric Attributes for Fast Object Recognition (L Grewe & A Kak)A Four Degree-of-Freedom Robot Head for Active Vision (F-L Du & M Brady)Control of Eye and Arm Movements Using Active, Attentional Vision (P A Sandon)Behavior-Based Active Vision (C S Pinhanez)
Readership: Computer scientists and engineers.
This book presents the latest advances in the principal fields that contribute to robotics. It contains contributions written by leading experts addressing topics such as Path and Motion Planning, Navigation and Sensing, Vision and Object Recognition, Environment Modeling, and others.
Contents:Path and Motion PlanningNavigation and SensingLocalization and VisibilityVision, Shape, and Object RecognitionEnvironment ModelingFixture Design and GraspingDistributed SystemsEcological Systems, Learning, and Robot ControlApplications
Readership: Researchers and scientists in intelligent robotics.
keywords:Path Planning;Motion Planning;Dynamical Systems;Navigation and Sensing;Localization;Visibility;Object Recognition;Environment Modeling;Spatial Representation;Fixture Design;Grasping;Distributed Systems;Learning and Skill Acquisition;Robot Control
Contents:Pattern Classification Techniques Based on Function Approximation (U Kressel & J Schürmann)Combination of Multiple Classifier Decisions for Optical Character Recognition (L Lam et al.)Segmentation-Based Cursive Handwriting Recognition (M Shridhar & F Kimura)Handwritten Word Recognition Using Hidden Markov Models (A Kundu)Techniques for Improving OCR Results (A Dengel et al.)Multilingual Document Recognition (A L Spitz)Arabic Character Recognition (A Amin)Interpretation of Engineering Drawings (K Tombre & D Dori)Automatic Reading of Music Notation (D Bainbridge & N Carter)Algorithms for Automatic Signature Verification (G Dimauro et al.)Automatic Reading of Braille Documents (A Antonacopoulos)Information Retrieval and OCR (K Taghva et al.)Benchmarking DIA Systems (T A Nartker et al.)and other papers
Readership: Computer scientists and engineers.
Readership: Computer scientists.
The contributions collected in this book present the state of the art in the field of complete systems for bankcheck recognition, and explore the most promising trends in key aspects of this research field.Contents:Automatic Bankcheck Processing: A New Engineered System (G Dimauro et al.)A Prototype for Brazilian Bankcheck Recognition (L L Lee et al.)Automatic Reading of Handwritten Amounts on French Checks (M Leroux et al.)Bankcheck Recognition Using Cross Validation Between Legal and Courtesy Amounts (G Kim & V Govindaraju)An Evolutionary Approach to the Use of Neural Networks in the Segmentation of Handwritten Numerals (J M Westall & M S Narasimha)An Off Line Cursive Handwritten Word Recognition System and Its Application to Legal Amount Interpretation (K Han & I K Sethi)Optimal Order of Markov Models Applied to Bankchecks (C Olivier et al.)A Cognitive Approach to Off-Line Signature Verification (N A Murshed et al.)and other papers
Readership: Students and researchers in artificial intelligence and employees of banks and other financial institutions.
See Additional Notes for instructions to download the highly interactive PC software. Used in thousands of schools and colleges worldwide the software is designed to work as an interactive textbook on your PC screen.
Comprising hundreds of menu selected colourful topics where the graphic images (from your eBook) are brought to life for every value change along with many additional learning software features.
A combined eBook and educational software package at a tiny fraction of the previously published price.
Chapters (958 topics): - Introduction, Electronics, Basic Electronics, DC Current Flow, Resistor Value Test, Simple DC Circuits, Types of Switching, Variable Voltages, Ohm's Law, DC Voltage, DC Current, Series/Parallel Resistors, AC Measurements, AC Voltage and Current, AC Theory, RCL Series Circuits, RCL Parallel Circuits, Capacitance, Capacitors, Inductance, Inductors, Impedance, Radio and Communication, Tuned Circuits, Attenuators, Passive Filters, Active Filters, Oscillators, Circuit Theorems, Complex Numbers, DC Power, AC Power, Silicon Controlled Rectifier, Power Supplies, Voltage Regulation, Magnetism, Electric Machines, Transformers, Three Phase Systems, Energy Transfer and Cost, Atomic Structures, Diode Theory, Diode Applications, Transistor Theory, Bipolar Transistor, Transistor Configurations, Active Transistor Circuits, Field Effect Transistors, Basic Operational Amplifier, Op-Amp Theory, Op-Amp Applications, Sum and Difference Amp, Analogue Multi-meter, Measurement, Component Testing, PIC Micro, PICa(R) Microcontroller, PICa(R) Architecture, PICa(R) Analogue to Digital, PICa(R) Byte Orientated Instructions, PICa(R) Bit Orientated Instructions, PICa(R) Literal and Control Instructions, Mechanics, Area, Surface Area and Symmetry, Volume, Compound Measures, Geometry, Motion, Machines, Optics, Computing, Hardware Devices, Data Structures, Data Files, Computer Systems, Data Handling, System Development, Computer Programming, Data Analysis, Binary Numbers, Binary Arithmetic, Digital, Logic Gates 1., Logic Gates 2., Logic Families, Flip Flops, Combinational Logic, Counters, Counting, Shift Registers, 555 Timer, Logic Interfacing, Boolean and DeMorgan's, Microprocessor, Micro-Computer, Data/Address Bus, Memory Addressing, Arithmetic and Logic Unit, Clock and Reset, Instructions and Control, Memory Cells, Microprocessor Memory, Addressing Modes, Instructions Set 1., Instructions Set 2., Instructions Set 3., Mathematics, Number Systems, Number Conversion, Number Types, Compound Measures, Roots, Angles and Parallels, Triangle Ratios, Triangle Angles, Percentages, Ratios, Fractions, Vectors, Circle Angles, Laws, Algebra 0., Algebra 1., Algebra 2., Mathematical Rules, Powers and Indices, Simplifying, Equations, Graphing, Slope and Translation, Curves and Angle Conversion, Personal Finance, Additional Notes.
Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today.By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us.
In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
This important guide/reference presents a comprehensive overview of medical image analysis. Highly practical in its approach, the text is uniquely structured by potential applications, supported by exercises throughout. Each of the key concepts are introduced in a concise manner, allowing the reader to understand the interdependencies between them before exploring the deeper details and derivations.
Topics and features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.
This easy-to-follow, classroom-tested textbook is ideal for undergraduate and graduate courses on medical image analysis and related subjects – with possible course outlines suggested in the Preface. The work can also be used as a self-study guide for professionals in medical imaging technology, and for computer scientists and engineers wishing to specialise in medical applications.
This book is unique in that it gives readers the skills necessary for obtaining excellent images for scientific purposes in a concise and procedurally oriented manner. This not only gets the reader used to a disciplined approach to imaging to maximize quality, but also to maximize the success (and minimize the frustration!) inherent in the pursuit of astrophotography. The knowledge and skills imparted to the reader of this handbook also provide an excellent basis for “beautiful picture” astrophotography!
There is a wealth of information in this book – a distillation of ideas and data presented by a diverse set of sources and based on the most recent techniques, equipment, and data available to the amateur astronomer. There are also numerous practical exercises. Scientific Astrophotography is perfect for any amateur astronomer who wants to go beyond just astrophotography and actually contribute to the science of astronomy.
The book covers the full range of the state of the art of NPR with every chapter authored by internationally renowned experts in the field, covering both classical and contemporary techniques. It will enable both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.
Written by leading experts in the field, this book presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms. It contains in-depth analysis of methods coupled with the results of specific real-world experiments. Microscope Image Processing covers image digitization and display, object measurement and classification, autofocusing, and structured illumination.
Key Features:Detailed descriptions of many leading-edge methods and algorithmsIn-depth analysis of the method and experimental results, taken from real-life examplesEmphasis on computational and algorithmic aspects of microscope image processingAdvanced material on geometric, morphological, and wavelet image processing, fluorescence, three-dimensional and time-lapse microscopy, microscope image enhancement, MultiSpectral imaging, and image data management
This book is of interest to all scientists, engineers, clinicians, post-graduate fellows, and graduate students working in the fields of biology, medicine, chemistry, pharmacology, and other related fields. Anyone who uses microscopes in their work and needs to understand the methodologies and capabilities of the latest digital image processing techniques will find this book invaluable.Presents a unique practical perspective of state-of-the-art microcope image processing and the development of specialized algorithmsEach chapter includes in-depth analysis of methods coupled with the results of specific real-world experimentsCo-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject
Ideal for enthusiasts, from students in robotics clubs to professional robotics scientists and engineers, each recipe describes a complete solution using ROS open source libraries and tools. You’ll learn how to complete tasks described in the recipes, as well as how to configure and recombine components for other tasks. If you’re familiar with Python, you’re ready to go.Learn fundamentals, including key ROS concepts, tools, and patternsProgram robots that perform an increasingly complex set of behaviors, using the powerful packages in ROSSee how to easily add perception and navigation abilities to your robotsIntegrate your own sensors, actuators, software libraries, and even a whole robot into the ROS ecosystemLearn tips and tricks for using ROS tools and community resources, debugging robot behavior, and using C++ in ROS
This book covers practical approach on software tools for ethical hacking. Some of the software tools covered are SQL Injection, Password Cracking, port scanning, packet sniffing and etc. Performing ethical hacking requires certain steps and procedures to be followed properly. A good ethical hacker will find information, identify weakness and finally perform some attacks on the target machine. Then the most crucial part would be to produce a good security audit report for the clients to understand their computer network conditions.
This book also explains and demonstrates step by step most of the software security tools for any beginners in the computer security field. Some of the software tools have been selected and utilized in computer security trainings and workshops.
Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in digital signal processing (speech and image processing), communication, computer science and mathematics. Wavelet transforms are known to have excellent energy compaction characteristics and are able to provide perfect reconstruction. Therefore, they are ideal for signal/image processing. The shifting (or translation) and scaling (or dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation.
The nature of wavelet computation forces us to carefully examine the implementation methodologies. As the computation of DWT involves filtering, an efficient filtering process is essential in DWT hardware implementation. In the multistage DWT, coefficients are calculated recursively, and in addition to the wavelet decomposition stage, extra space is required to store the intermediate coefficients. Hence, the overall performance depends significantly on the precision of the intermediate DWT coefficients.This work presents new implementation techniques of DWT, that are efficient in terms of computation requirement, storage requirement, and with better signal-to-noise ratio in the reconstructed signal.
The book proposes novel 3D feature representations called Point Feature Histograms (PFH), as well as a frameworks for the acquisition and processing of Semantic 3D Object Maps with contributions to robust registration, fast segmentation into regions, and reliable object detection, categorization, and reconstruction. These contributions have been fully implemented and empirically evaluated on different robotic systems, and have been the original kernel to the widely successful open-source project the Point Cloud Library (PCL) -- see http://pointclouds.org.
You will learn how to use React completely, and learn best practices for creating interfaces in a composable way. You will also cover additional tools and libraries in the React ecosystem (such as React Router and Flux architecture). Each topic is covered clearly and concisely and is packed with the details you need to learn to be truly effective. The most important features are given no-nonsense, in-depth treatment, and every chapter details common problems and how to avoid them.
Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiarizes readers with the most commonly used data structures and their algorithms, and discusses matching appropriate data structures to applications. The author offers explicit coverage of design patterns encountered in the course of programming the book's basic data structures and algorithms. Numerous examples appear throughout the text.
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.
Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
“Lessons from the Masters” includes a brilliant body of recognized leaders in astronomical imaging, assembled by Robert Gendler, who delivers the most current, sophisticated and useful information on digital enhancement techniques in astrophotography available today. Each chapter focuses on a particular technique, but the book as a whole covers all types of astronomical image processing, including processing of events such as eclipses, using DSLRs, and deep-sky, planetary, widefield, and high resolution astronomical image processing. Recognized contributors include deep-sky experts such as Jay GaBany, Tony Hallas, and Ken Crawford, high-resolution planetary expert Damian Peach, and the founder of TWAN (The World at Night) Babak A. Tafreshi.
A large number of illustrations (150, 75 in color) present the challenges and accomplishments involved in the processing of astronomical images by enthusiasts.
Based on the bestselling first and second editions, Beginning Ruby, Third Edition is a leading guide to learn Ruby from the ground up. The new edition of this book provides the same excellent introduction to Ruby as the previous editions plus updates for the newest version of Ruby 2.3. This book can also be used as a textbook or companion to a textbook on beginning Ruby programming.
The light and agile Ruby programming language remains a very popular open source scripting option for developers building today's web and even some enterprise applications. And, now, Ruby also has applications using the Raspberry Pi, popular among hobbyists and makers. Many former Java developers still use Ruby on Rails today, the most popular framework for building Ruby applications.
What You'll LearnDiscover the fundamentals of Ruby and its object-oriented building blocksUse the Ruby libraries, gems, and documentationWork with files and databasesWrite and deploy Ruby applicationsHarness the various Ruby web frameworks and how to use themDo network programming with Ruby Who This Book Is For
Beginning programmers, programmers new to Ruby, and web developers interested in learning and knowing the foundations of the Ruby programming language.
The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications such virtual fitting rooms, training for athletes, and assistance for the elderly. This authoritative text/reference reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications.
Topics and features: presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research; addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points; examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing; provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition; with a Foreword by Dr. Jamie Shotton of Microsoft Research, Cambridge, UK.
This broad-ranging overview is a must-read for researchers and graduate students of computer vision and robotics wishing to learn more about the state of the art of this increasingly “hot” topic.
Chances are you already use Excel to perform some fairly routine calculations. Now the Excel Scientific and Engineering Cookbook shows you how to leverage Excel to perform more complex calculations, too, calculations that once fell in the domain of specialized tools. It does so by putting a smorgasbord of data analysis techniques right at your fingertips. The book shows how to perform these useful tasks and others:Use Excel and VBA in generalImport data from a variety of sourcesAnalyze dataPerform calculationsVisualize the results for interpretation and presentationUse Excel to solve specific science and engineering problems
Wherever possible, the Excel Scientific and Engineering Cookbook draws on real-world examples from a range of scientific disciplines such as biology, chemistry, and physics. This way, you'll be better prepared to solve the problems you face in your everyday scientific or engineering tasks.
High on practicality and low on theory, this quick, look-up reference provides instant solutions, or "recipes," to problems both basic and advanced. And like other books in O'Reilly's popular Cookbook format, each recipe also includes a discussion on how and why it works. As a result, you can take comfort in knowing that complete, practical answers are a mere page-flip away.
Vein Pattern Recognition: A Privacy-Enhancing Biometric provides a comprehensive and practical look at biometrics in general and at vein pattern recognition specifically. It discusses the emergence of this reliable but underutilized technology and evaluates its capabilities and benefits. The author, Chuck Wilson, an industry veteran with more than 25 years of experience in the biometric and electronic security fields, examines current and emerging VPR technology along with the myriad applications of this dynamic technology. Wilson explains the use of VPR and provides an objective comparison of the different biometric methods in use today—including fingerprint, eye, face, voice recognition, and dynamic signature verification.
Highlighting current VPR implementations, including its widespread acceptance and use for identity verification in the Japanese banking industry, the text provides a complete examination of how VPR can be used to protect sensitive information and secure critical facilities. Complete with best-practice techniques, the book supplies invaluable guidance on selecting the right combination of biometric technologies for specific applications and on properly implementing VPR as part of an overall security system.
Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
The Silicon Jungle is a cautionary fictional tale of data mining’s promise and peril. Baluja raises ethical questions about contemporary technological innovations, and how minute details can be routinely pieced together into rich profiles that reveal our habits, goals, and secret desires—all ready to be exploited.
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.
More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques
Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book Supplies supplementary course material for students at the associated website, http://szeliski.org/Book/
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
This book addresses important aspects and fundamental concepts in hydrocarbon exploration and production. Moreover, new developments and recent advances in the relevant research areas are discussed, whereby special emphasis is placed on mathematical methods and modelling. The book reflects the multi-disciplinary character of the hydrocarbon production workflow, ranging from seismic data imaging, seismic analysis and interpretation and geological model building, to numerical reservoir simulation. Various challenges concerning the production workflow are discussed in detail.
The thirteen chapters of this joint work, authored by international experts from academic and industrial institutions, include survey papers of expository character as well as original research articles. Large parts of the material presented in this book were developed between November 2000 and April 2004 through the European research and training network NetAGES, "Network for Automated Geometry Extraction from Seismic". The new methods described here are currently being implemented as software tools at Schlumberger Stavanger Research, one of the world's largest service providers to the oil industry.
See Additional Notes for instructions to download the highly interactive PC software for your school. Used in thousands of schools and colleges worldwide the software is designed to work as a traditional textbook on your PC screen.
Comprising hundreds of menu selected colourful topics where the graphic images (from your eBook) are brought to life for every value change along with many additional learning software features.
Full colour printed is available for student handouts (using your values and selections) or images and text pasted to make student assignments.
Various additional software editors are included to enable your own calculations to be explored and evaluated from simple algebraic equations to complex formulae.
A combined eBook and educational software package at a tiny fraction of the previously published price.
Table of Contents (350 software topics) Introduction, Hardware Devices, Data Structures, Data Files, Computer Systems, Data Handling, System Development, Computer Programming, Binary Numbers, Binary Arithmetic, Logic Gates 1., Logic Gates 2., Logic Families, Flip Flops, Combinational Logic, Counters, Counting, Shift Registers, Logic Interfacing, Boolean and DeMorgan's, Micro-Computer, Data/Address Bus, Memory Addressing, Arithmetic and Logic Unit, Clock and Reset, Instructions and Control, Memory Cells, Microprocessor Memory, Addressing Modes, Instructions Set 1., Instructions Set 2., Instructions Set 3., Additional Notes.
The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals of robot kinematics, dynamics and joint level control, then camera models, image processing, feature extraction and epipolar geometry, and bring it all together in a visual servo system.
Additional material is provided at http://www.petercorke.com/RVC
Beginning Java Game Development with LibGDX teaches by example with many game case study projects that you will build throughout the book. This ensures that you will see all of the APIs that are encountered in the book in action and learn to incorporate them into your own projects. The book also focuses on teaching core Java programming concepts and applying them to game development.
What You Will LearnHow to use the LibGDX framework to create a host of 2D arcade game case studies
How to compile your game to run on multiple platforms, such as iOS, Android, Windows, and MacOS
How to incorporate different control schemes, such as touchscreen, gamepad, and keyboard
Who This Book Is ForReaders should have an introductory level knowledge of basic Java programming. In particular, you should be familiar with: variables, conditional statements, loops, and be able to write methods and classes to accomplish simple tasks. This background is equivalent to having taken a first-semester college course in Java programming.