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Books > Computing & IT > Applications of computing > Pattern recognition

Essentials of Pattern Recognition - An Accessible Approach (Hardcover): Jianxin Wu Essentials of Pattern Recognition - An Accessible Approach (Hardcover)
Jianxin Wu
R1,260 Discovery Miles 12 600 Ships in 10 - 15 working days

This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples. Concepts are reinforced with hands-on exercises to nurture the student's skill in problem solving. New concepts and algorithms are framed by real-world context and established as part of the big picture introduced in an early chapter. A problem-solving strategy is employed in several chapters to equip students with an approach for new problems in pattern recognition. This text also points out common errors that a new player in pattern recognition may encounter, and fosters the ability for readers to find useful resources and independently solve a new pattern recognition task through various working examples. Students with an undergraduate understanding of mathematical analysis, linear algebra, and probability will be well prepared to master the concepts and mathematical analysis presented here.

High-Dimensional Statistics - A Non-Asymptotic Viewpoint (Hardcover): Martin J Wainwright High-Dimensional Statistics - A Non-Asymptotic Viewpoint (Hardcover)
Martin J Wainwright
R1,517 Discovery Miles 15 170 Ships in 10 - 15 working days

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.

Computer Vision -- ACCV 2009 - 9th Asian Conference on Computer Vision, Xi'an, China, September 23-27, 2009, Revised... Computer Vision -- ACCV 2009 - 9th Asian Conference on Computer Vision, Xi'an, China, September 23-27, 2009, Revised Selected Papers, Part II (Paperback, Edition.)
Hongbin Zha, Rin-Ichiro Taniguchi, Stephen Maybank
R3,881 Discovery Miles 38 810 Ships in 7 - 11 working days

It givesus greatpleasureto presentthe proceedings of the 9th Asian Conference on Computer Vision (ACCV 2009), held in Xi'an, China, in September 2009. This was the ?rst ACCV conference to take place in mainland China. We received a total of 670 full submissions, which is a new record in the ACCV series. Overall, 35 papers were selected for oral presentation and 131 as posters, yielding acceptance rates of 5.2% for oral, 19.6% for poster, and 24.8% in total. In the paper reviewing, we continued the tradition of previous ACCVsbyconductingtheprocessinadouble-blindmanner.Eachofthe33Area Chairs received a pool of about 20 papers and nominated a number of potential reviewers for each paper. Then, Program Committee Chairs allocated at least three reviewers to each paper, taking into consideration any con?icts of interest and the balance of loads. Once the reviews were ?nished, the Area Chairs made summaryreportsforthepapersintheirpools,basedonthereviewers'comments and on their own assessments of the papers.

Mathematics for Machine Learning (Paperback): Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Mathematics for Machine Learning (Paperback)
Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
R1,008 Discovery Miles 10 080 Ships in 10 - 15 working days

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Advances in Dynamics, Patterns, Cognition - Challenges in Complexity (Hardcover, 1st ed. 2017): Igor S. Aranson, Arkady... Advances in Dynamics, Patterns, Cognition - Challenges in Complexity (Hardcover, 1st ed. 2017)
Igor S. Aranson, Arkady Pikovsky, Nikolai F. Rulkov, Lev S. Tsimring
R4,944 Discovery Miles 49 440 Ships in 7 - 11 working days

This book focuses on recent progress in complexity research based on the fundamental nonlinear dynamical and statistical theory of oscillations, waves, chaos, and structures far from equilibrium. Celebrating seminal contributions to the field by Prof. M. I. Rabinovich of the University of California at San Diego, this volume brings together perspectives on both the fundamental aspects of complexity studies, as well as in applications in different fields ranging from granular patterns to understanding of the cognitive brain and mind dynamics. The slate of world-class authors review recent achievements that together present a broad and coherent coverage of modern research in complexity greater than the sum of its parts.

Real-Time Recursive Hyperspectral Sample and Band Processing - Algorithm Architecture and Implementation (Hardcover, 1st ed.... Real-Time Recursive Hyperspectral Sample and Band Processing - Algorithm Architecture and Implementation (Hardcover, 1st ed. 2017)
Chein-I Chang
R5,405 Discovery Miles 54 050 Ships in 7 - 11 working days

This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author's books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016.

Machine Learning Refined - Foundations, Algorithms, and Applications (Hardcover, 2nd Revised edition): Jeremy Watt, Reza... Machine Learning Refined - Foundations, Algorithms, and Applications (Hardcover, 2nd Revised edition)
Jeremy Watt, Reza Borhani, Aggelos K. Katsaggelos
R1,468 Discovery Miles 14 680 Ships in 10 - 15 working days

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.

Computer Vision -- ACCV 2009 - 9th Asian Conference on Computer Vision, Xi'an, China, September 23-27, 2009, Revised... Computer Vision -- ACCV 2009 - 9th Asian Conference on Computer Vision, Xi'an, China, September 23-27, 2009, Revised Selected Papers, Part I (Paperback, Edition.)
Hongbin Zha, Rin-Ichiro Taniguchi, Stephen Maybank
R2,788 Discovery Miles 27 880 Ships in 7 - 11 working days

It gives us greatpleasureto presentthe proceedings of the 9th Asian Conference on Computer Vision (ACCV 2009), held in Xi'an, China, in September 2009. This was the ?rst ACCV conference to take place in mainland China. We received a total of 670 full submissions, which is a new record in the ACCV series. Overall, 35 papers were selected for oral presentation and 131 as posters, yielding acceptance rates of 5.2% for oral, 19.6% for poster, and 24.8% in total. In the paper reviewing, we continued the tradition of previous ACCVsbyconductingthe processinadouble-blindmanner.Eachofthe33Area Chairs received a pool of about 20 papers and nominated a number of potential reviewers for each paper. Then, Program Committee Chairs allocated at least three reviewers to each paper, taking into consideration any con?icts of interest and the balance of loads. Once the reviews were ?nished, the Area Chairs made summaryreportsforthepapersintheirpools,basedonthereviewers'comments and on their own assessments of the papers.

Pattern Recognition - Practices, Perspectives & Challenges (Hardcover): Darrell B Vincent Pattern Recognition - Practices, Perspectives & Challenges (Hardcover)
Darrell B Vincent
R3,821 Discovery Miles 38 210 Ships in 10 - 15 working days

In this work, the authors present current research in the study of the practices, perspectives and challenges of pattern recognition. The topics include the practical usage of algorithmic probability in pattern recognition; application of pattern recognition in optimisation-simulation techniques; pattern recognition applied to spectroscopy; optimisation of an embedded simplified fuzzy ARTMAP implemented on a microcontroller using MATLAB GUI environment; pattern recognition using quaternion colour moments; and pattern recognition by Bessel mask and one-dimensional signatures.

Analytic Pattern Matching - From DNA to Twitter (Hardcover, New title): Philippe Jacquet, Wojciech Szpankowski Analytic Pattern Matching - From DNA to Twitter (Hardcover, New title)
Philippe Jacquet, Wojciech Szpankowski
R1,397 Discovery Miles 13 970 Ships in 10 - 15 working days

How do you distinguish a cat from a dog by their DNA? Did Shakespeare really write all of his plays? Pattern matching techniques can offer answers to these questions and to many others, from molecular biology, to telecommunications, to classifying Twitter content. This book for researchers and graduate students demonstrates the probabilistic approach to pattern matching, which predicts the performance of pattern matching algorithms with very high precision using analytic combinatorics and analytic information theory. Part I compiles known results of pattern matching problems via analytic methods. Part II focuses on applications to various data structures on words, such as digital trees, suffix trees, string complexity and string-based data compression. The authors use results and techniques from Part I and also introduce new methodology such as the Mellin transform and analytic depoissonization. More than 100 end-of-chapter problems help the reader to make the link between theory and practice.

Pattern Recognition in Computational Molecular Biology - Techniques and Approaches (Hardcover): Mourad Elloumi, Costas... Pattern Recognition in Computational Molecular Biology - Techniques and Approaches (Hardcover)
Mourad Elloumi, Costas Iliopoulos, Jason T.L. Wang, Albert Y. Zomaya
R2,815 R2,663 Discovery Miles 26 630 Save R152 (5%) Ships in 10 - 15 working days

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. * Surveys the development of techniques and approaches on pattern recognition in biomolecular data * Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks * Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.

Proceedings of 2nd International Conference on Computer Vision & Image Processing - CVIP 2017, Volume 1 (Paperback, 1st ed.... Proceedings of 2nd International Conference on Computer Vision & Image Processing - CVIP 2017, Volume 1 (Paperback, 1st ed. 2018)
Bidyut B. Chaudhuri, Mohan S. Kankanhalli, Balasubramanian Raman
R5,478 Discovery Miles 54 780 Ships in 7 - 11 working days

The book provides insights into the Second International Conference on Computer Vision & Image Processing (CVIP-2017) organized by Department of Computer Science and Engineering of Indian Institute of Technology Roorkee. The book presents technological progress and research outcomes in the area of image processing and computer vision. The topics covered in this book are image/video processing and analysis; image/video formation and display; image/video filtering, restoration, enhancement and super-resolution; image/video coding and transmission; image/video storage, retrieval and authentication; image/video quality; transform-based and multi-resolution image/video analysis; biological and perceptual models for image/video processing; machine learning in image/video analysis; probability and uncertainty handling for image/video processing; motion and tracking; segmentation and recognition; shape, structure and stereo.

Animal Biometrics - Techniques and Applications (Hardcover, 1st ed. 2017): Santosh Kumar, Sanjay Kumar Singh, Rishav Singh,... Animal Biometrics - Techniques and Applications (Hardcover, 1st ed. 2017)
Santosh Kumar, Sanjay Kumar Singh, Rishav Singh, Amit Kumar Singh
R2,385 Discovery Miles 23 850 Ships in 7 - 11 working days

This book presents state-of-the-art methodologies and a comprehensive introduction to the recognition and representation of species and individual animals based on their physiological and phenotypic appearances, biometric characteristics, and morphological image patterns. It provides in-depth coverage of this emerging area, with an emphasis on the design and analysis techniques used in visual animal biometrics-based recognition systems. The book offers a comprehensive introduction to visual animal biometrics, addressing a range of recent advances and practices like sensing, feature extraction, feature selection and representation, matching, indexing of feature sets, and animal biometrics-based multimodal systems. It provides authoritative information on all the major concepts, as well as highly specific topics, e.g. the identification of cattle based on their muzzle point image pattern and face images to prevent false insurance claims, or the monitoring and registration of animals based on their biometric features. As such, the book provides a sound platform for understanding the Visual Animal Biometrics paradigm, a vital catalyst for researchers in the field, and a valuable guide for professionals. In addition, it can help both private and public organizations adapt and enhance their classical animal recognition systems.

Introduction to Intelligent Surveillance - Surveillance Data Capture, Transmission, and Analytics (Hardcover, 2nd ed. 2017):... Introduction to Intelligent Surveillance - Surveillance Data Capture, Transmission, and Analytics (Hardcover, 2nd ed. 2017)
Weiqi Yan
R2,282 Discovery Miles 22 820 Ships in 7 - 11 working days

This accessible textbook/reference reviews the fundamental concepts and practical issues involved in designing digital surveillance systems that fully exploit the power of intelligent computing techniques. The book presents comprehensive coverage of all aspects of such systems, from camera calibration and data capture, to the secure transmission of surveillance data. In addition to the detection and recognition of objects and biometric features, the text also examines the automated observation of surveillance events, and how this can be enhanced through the use of deep learning methods and supercomputing technology. This updated new edition features extended coverage on face detection, pedestrian detection and privacy preservation for intelligent surveillance. Topics and features: contains review questions and exercises in every chapter, together with a glossary; describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics; examines the importance of network security and digital forensics in the communication of surveillance data, as well as issues of issues of privacy and ethics; discusses the Viola-Jones object detection method, and the HOG algorithm for pedestrian and human behavior recognition; reviews the use of artificial intelligence for automated monitoring of surveillance events, and decision-making approaches to determine the need for human intervention; presents a case study on a system that triggers an alarm when a vehicle fails to stop at a red light, and identifies the vehicle's license plate number; investigates the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing. This concise, classroom-tested textbook is ideal for undergraduate and postgraduate-level courses on intelligent surveillance. Researchers interested in entering this area will also find the book suitable as a helpful self-study reference.

Mining of Massive Datasets (Hardcover, 3rd Revised edition): Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman Mining of Massive Datasets (Hardcover, 3rd Revised edition)
Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman
R1,542 Discovery Miles 15 420 Ships in 10 - 15 working days

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Visual Attributes (Hardcover, 1st ed. 2017): Rogerio Schmidt Feris, Christoph Lampert, Devi Parikh Visual Attributes (Hardcover, 1st ed. 2017)
Rogerio Schmidt Feris, Christoph Lampert, Devi Parikh
R4,591 Discovery Miles 45 910 Ships in 7 - 11 working days

This unique text/reference provides a detailed overview of the latest advances in machine learning and computer vision related to visual attributes, highlighting how this emerging field intersects with other disciplines, such as computational linguistics and human-machine interaction. Topics and features: presents attribute-based methods for zero-shot classification, learning using privileged information, and methods for multi-task attribute learning; describes the concept of relative attributes, and examines the effectiveness of modeling relative attributes in image search applications; reviews state-of-the-art methods for estimation of human attributes, and describes their use in a range of different applications; discusses attempts to build a vocabulary of visual attributes; explores the connections between visual attributes and natural language; provides contributions from an international selection of world-renowned scientists, covering both theoretical aspects and practical applications.

Combining Pattern Classifiers - Methods and Algorithms (Hardcover, 2nd Edition): Ludmila I. Kuncheva Combining Pattern Classifiers - Methods and Algorithms (Hardcover, 2nd Edition)
Ludmila I. Kuncheva
R2,275 R2,160 Discovery Miles 21 600 Save R115 (5%) Ships in 10 - 15 working days

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods. Thoroughly updated, with MATLAB(R) code and practice data sets throughout, Combining Pattern Classifiers includes: * Coverage of Bayes decision theory and experimental comparison of classifiers * Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others * Chapters on classifier selection, diversity, and ensemble feature selection With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.

Introduction to Applied Linear Algebra - Vectors, Matrices, and Least Squares (Hardcover): Stephen Boyd, Lieven Vandenberghe Introduction to Applied Linear Algebra - Vectors, Matrices, and Least Squares (Hardcover)
Stephen Boyd, Lieven Vandenberghe
R968 Discovery Miles 9 680 Ships in 10 - 15 working days

This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB (R), and data sets accompanying the book online. Suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.

Observations, Modeling and Systems Analysis in Geomagnetic Data Interpretation (Hardcover, 1st ed. 2020): Alexei Gvishiani,... Observations, Modeling and Systems Analysis in Geomagnetic Data Interpretation (Hardcover, 1st ed. 2020)
Alexei Gvishiani, Anatoly Soloviev
R3,228 Discovery Miles 32 280 Ships in 7 - 11 working days

Geomagnetic field penetrates through all shells of the solid Earth, hydrosphere and atmosphere, spreading into space. The Earth Magnetic Field plays a key-role in major natural processes. Geomagnetic field variations in time and space provide important information about the state of the solid Earth, as well as the solar-terrestrial relationships and space weather conditions. The monograph presents a set of fundamental and, at the same time, urgent scientific problems of modern geomagnetic studies, as well as describes the results of the authors' developments. The new technique introduced in the book can be applied far beyond the limits of Earth sciences. Requirements to corresponding data models are formulated. The conducted experimental investigations are combined with development and implementation of new methods of mathematical modeling, artificial intelligence, systems analysis and data science to solve the fundamental problems of geomagnetism. At that, formalism of Big Data and its application to Earth Sciences is presented as essential part of systems analysis. The book is intended for research scientists, tutors, students, postgraduate students and engineers working in geomagnetism and Earth sciences in general, as well as in other relevant scientific disciplines.

Moments and Moment Invariants in Pattern Recognition (Hardcover): Jan Flusser, Barbara Zitova, Tomas Suk Moments and Moment Invariants in Pattern Recognition (Hardcover)
Jan Flusser, Barbara Zitova, Tomas Suk
R2,283 R2,167 Discovery Miles 21 670 Save R116 (5%) Ships in 10 - 15 working days

Moments as projections of an image's intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging.

Key features:

Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms - translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course.

"Moments and Moment Invariants in Pattern Recognition" is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.

Digital Human Modeling - Second International Conference, ICDHM 2009, Held as Part of HCI International 2009 San Diego, CA,... Digital Human Modeling - Second International Conference, ICDHM 2009, Held as Part of HCI International 2009 San Diego, CA, USA, July 19-24, 2009 Proceedings (Paperback, 2009 ed.)
Vincent G. Duffy
R3,882 Discovery Miles 38 820 Ships in 7 - 11 working days

The 13th International Conference on Human-Computer Interaction, HCI Inter- tional 2009, was held in San Diego, California, USA, July 19-24, 2009, jointly with the Symposium on Human Interface (Japan) 2009, the 8th International Conference on Engineering Psychology and Cognitive Ergonomics, the 5th International Conference on Universal Access in Human-Computer Interaction, the Third International Conf- ence on Virtual and Mixed Reality, the Third International Conference on Internati- alization, Design and Global Development, the Third International Conference on Online Communities and Social Computing, the 5th International Conference on Augmented Cognition, the Second International Conference on Digital Human Mod- ing, and the First International Conference on Human Centered Design. A total of 4,348 individuals from academia, research institutes, industry and gove- mental agencies from 73 countries submitted contributions, and 1,397 papers that were judged to be of high scientific quality were included in the program. These papers - dress the latest research and development efforts and highlight the human aspects of the design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas.

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part I (Paperback, 1st ed. 2020)
Alessandro Crimi, Spyridon Bakas
R1,988 Discovery Miles 19 880 Ships in 7 - 11 working days

The two-volume set LNCS 11992 and 11993 constitutes the thoroughly refereed proceedings of the 5th International MICCAI Brainlesion Workshop, BrainLes 2019, the International Multimodal Brain Tumor Segmentation (BraTS) challenge, the Computational Precision Medicine: Radiology-Pathology Challenge on Brain Tumor Classification (CPM-RadPath) challenge, as well as the tutorial session on Tools Allowing Clinical Translation of Image Computing Algorithms (TACTICAL). These were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI, in Shenzhen, China, in October 2019. The revised selected papers presented in these volumes were organized in the following topical sections: brain lesion image analysis (12 selected papers from 32 submissions); brain tumor image segmentation (57 selected papers from 102 submissions); combined MRI and pathology brain tumor classification (4 selected papers from 5 submissions); tools allowing clinical translation of image computing algorithms (2 selected papers from 3 submissions.)

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part II (Paperback, 1st ed. 2020)
Alessandro Crimi, Spyridon Bakas
R1,988 Discovery Miles 19 880 Ships in 7 - 11 working days

The two-volume set LNCS 11992 and 11993 constitutes the thoroughly refereed proceedings of the 5th International MICCAI Brainlesion Workshop, BrainLes 2019, the International Multimodal Brain Tumor Segmentation (BraTS) challenge, the Computational Precision Medicine: Radiology-Pathology Challenge on Brain Tumor Classification (CPM-RadPath) challenge, as well as the tutorial session on Tools Allowing Clinical Translation of Image Computing Algorithms (TACTICAL). These were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI, in Shenzhen, China, in October 2019. The revised selected papers presented in these volumes were organized in the following topical sections: brain lesion image analysis (12 selected papers from 32 submissions); brain tumor image segmentation (57 selected papers from 102 submissions); combined MRI and pathology brain tumor classification (4 selected papers from 5 submissions); tools allowing clinical translation of image computing algorithms (2 selected papers from 3 submissions.)

Statistical Pattern Recognition (Hardcover, 3rd Edition): Andrew R. Webb, Keith D. Copsey Statistical Pattern Recognition (Hardcover, 3rd Edition)
Andrew R. Webb, Keith D. Copsey
R2,513 R2,384 Discovery Miles 23 840 Save R129 (5%) Ships in 10 - 15 working days

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques.

This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples.

"Statistical Pattern Recognition," 3rd Edition: Provides a self-contained introduction to statistical pattern recognition.Includes new material presenting the analysis of complex networks.Introduces readers to methods for Bayesian density estimation.Presents descriptions of new applications in biometrics, security, finance and condition monitoring.Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applicationsDescribes mathematically the range of statistical pattern recognition techniques.Presents a variety of exercises including more extensive computer projects.

The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. "Statistical Pattern Recognition" is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields.

www.wiley.com/go/statistical_pattern_recognition

Progress in Pattern Recognition (Hardcover): Sameer Singh, Maneesha Singh Progress in Pattern Recognition (Hardcover)
Sameer Singh, Maneesha Singh
R4,626 Discovery Miles 46 260 Ships in 7 - 11 working days

The field of pattern recognition has emerged as one of the most challenging and important endeavours in the area of information technology research. Research in the area of pattern recognition has benefits for improving many areas of human endeavour, including medicine, the economy, the environment, and security. This book presents some of the latest advances in the area of pattern recognition theory and applications. The first half of the book discusses novel pattern classification and matching schemes, and the second half describes the application of novel tools in biometrics and digital multimedia. The applications included, such as face/iris recognition, handwriting recognition, surveillance, human dynamics, sensor fusion, etc., provide a detailed insight into how to build real pattern recognition systems and how to evaluate them. Given the dynamic nature of technology evolution in this area, this book provides the latest algorithms and concepts that can be used to build real systems. Features and topics: Provides state-of-the art algorithms, as well as presents cutting-edge applications within the field Introduces achievements in theoretical pattern recognition, including statistical and Bayesian pattern recognition, structural pattern recognition, neural networks, classification and data mining, evolutionary approaches to optimisation, and knowledge based systems Offers insights and support to practitioners concerned with the state-of-the art technology in the area Progress in Pattern Recognition addresses the needs of postgraduate students, researchers, and practitioners in the areas of computer science, engineering and mathematicswhere pattern recognition techniques are widely used. Professor Sameer Singh is Director of the Research School of Informatics, Loughborough University, UK, and serves as Editor-in-Chief of the Springer journal, Pattern Analysis and Applications.

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