applied pattern recognition (68 Ergebnisse)

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Softcover. Zustand: gut. 1997. Bildverarbeitung C++ Programmiersprache Efficient Algorithms Informatik EDV Image Processing Inheritance Mustererkennung Pattern Analysis pattern recognition Program Design programming software development Speech processing Spracherkennung statistical pattern recognition "Ein ganz großer Vorteil dieses Buches ist, dass die Thematik nicht nur auf einer abstrakten Ebene beschrieben wird, sondern dass im Buch immer wieder die Umsetzung der Aussagen in C++ gezeigt wird. neben einer Einführung in C++ werden die Algorithmen und Techniken immer wieder auch als Programm vorgestellt. Dadurch wird der Schritt von der Theorie - das heißt, dem als mathematische Formel beschriebenen Algorithmus - hin zur Praxis (dem Computerprogramm) durchgängig." Elektronik This book demonstrates the efficiency of the C++ programming language in the realm of pattern recognition and pattern analysis. For this 3rd edition, new features of the C++ language were integrated and their relevance for image and speech processing is discussed. The description of the STL library was extended and STL is now used in many places in the book. The chapters 23 and 24 can now be used to build complete systems and give hints for further extensions.The book is divided into 4 parts. After an introduction to programming and software engineering, the required basics of image and speech processing are given. Statistics and mathematics is explained as required. The second part treats C++ as an object-oriented language and introduces it thru examples. In the third part the examples of the first and second part are combined to form an image segmentation and a word recognition system. All relevant features of the C++ language are thus introduced with direct relation to the tasks in image and speech processing. "Die Behandlung der C++-Konstukte ist wirklich anwendungsnah." Prof. Dr. Michael Schenke, FH Merseburg "// sehr umfassend - anschaulich, klar, gut nachvollziehbar." Prof. Dr.-Ing. Hans Peter Kölzer, HAW Hamburg "Dieses Buch werde ich meinen Studenten empfehlen, weil es einen sehr anschaulichen und motivierenden Einstieg in die Mustererkennung bietet." Prof. Dr. Hans-Peter Weber, FH Darmstadt Concerning 3rd edition: "This book is a beautifully arranged marriage of state-of-the-art pattern recognition theory and of programming theory and practice. The elegant and thorough treatment of modern aspects of speech and video processing and interpretation springs to life through a multitude of well-designed case studies and concrete examples." Carlo Tomasi, Prof. of Computer Science, Duke University, USA "This book is a must for learners of practical image processing. The examples are well explained and cover the needs of a graduate image processing or pattern recognition course." Laszlo Csink, Prof. of Computer Science, Budapest Polytechnic John von Neumann Faculty of Informatics, Hungary "I am not aware of a book comparable to this one which gives an excellent combination of an account of relevant topics in pattern recognition as well as of techniques for implementing the equations and algorithms in C++. Therefore, the book is invaluable both to students starting in the field and and to practitioners needing a special algorithm and its implementation." H. Niemann, Prof. of Computer Science, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany "// this book has been the perfect source for my students and me. Not only that the reader is elegantly and in a straightforward manner guided to the central points of the theory, but in parallel the authors also make it transparent how to implement the algorithms resulting from the theory." Volkmar Welker, Prof. of Discrete Mathematics, University of Marburg, Germany Applied Pattern RecognitionA Practical Introduction to Image and Speech Processing in C++ Joachim Hornegger Dietrich W. R. Paulus Bildbearbeitung Bildverarbeitung Grafik EDV C++ Theorie Software-Entwicklung Mustererkennung Spracherkennung Vieweg+Teubner In englischer Sprache. 403 pages. 20,3 x 15,2 x 2,5 cm.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 28th International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2024, and the 23rd International Conference on Information and Knowledge Engineering, IKE 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024.The 19 IPCV 2024 papers included in these proceedings were carefully reviewed and selected from 98 submissions. IKE 2024 received 40 submissions and accepted 10 papers for inclusion in the proceedings.The papers have been organized in topical sections as follows: Image processing, computer vision and pattern recognition; image processing, computer vision and pattern recognition - detection methods; and information and knowledge engineering.

Taschenbuch. Zustand: Neu. Neuware -Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the ¿four-color problem¿ posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber ¿ g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds.

Zustand: Gut. Zustand: Gut | Seiten: 201 | Sprache: Englisch | Produktart: Bücher.

Softcover. Zustand: gut. 1995. Bildverarbeitung C++ Programmiersprache Efficient Algorithms Informatik EDV Image Processing Inheritance Mustererkennung Pattern Analysis pattern recognition Program Design programming software development Speech processing Spracherkennung statistical pattern recognition Provides an introduction to applications and problems from the field of pattern recognition. Basic topics and the mathematical background of image and speech processing are described. Algorithms and data structures for filtering, feature extraction, segmentation and classification are discussed.This work provides an instructive into applications and problems from the broad field of pattern recognition. It describes basic topics and the required mathematical background of image and speech processing. Algorithms and data structures for filtering, feature extraction, segmentation and classification are discussed, introducing and demonstrating different C++ concepts. The practice of object-oriented programming is illustrated by a step-wise development of a complete class library for image processing. Part 1 Introductions: pattern recognition; from C to C++; software development; expressions, statements, functions; classification and pattern analysis; arrays and pointers; statistics for pattern recognition; C++ as a better C. Part 2 Object-oriented pattern analysis: object-oriented programming; classes in C++; intensity images; inheritance in C++-classes; edge detection and edge images; class libraries; hierarchy of picture processing objects; spectral features and speech processing. Part 3 Pattern recognition algorithms: an image analysis system; synthetic signals and images; filtering and smoothing signals; histogram algorithms; edge images; line detection algorithms; chain codes. Appendices: basics of C++; software development tools; source codes and tools. Ein ganz großer Vorteil dieses Buches ist, dass die Thematik nicht nur auf einer abstrakten Ebene beschrieben wird, sondern dass im Buch immer wieder die Umsetzung der Aussagen in C++ gezeigt wird. neben einer Einführung in C++ werden die Algorithmen und Techniken immer wieder auch als Programm vorgestellt. Dadurch wird der Schritt von der Theorie - das heißt, dem als mathematische Formel beschriebenen Algorithmus - hin zur Praxis (dem Computerprogramm) durchgängig." Elektronik This book demonstrates the efficiency of the C++ programming language in the realm of pattern recognition and pattern analysis. For this 3rd edition, new features of the C++ language were integrated and their relevance for image and speech processing is discussed. The description of the STL library was extended and STL is now used in many places in the book. The chapters 23 and 24 can now be used to build complete systems and give hints for further extensions.The book is divided into 4 parts. After an introduction to programming and software engineering, the required basics of image and speech processing are given. Statistics and mathematics is explained as required. The second part treats C++ as an object-oriented language and introduces it thru examples. In the third part the examples of the first and second part are combined to form an image segmentation and a word recognition system. All relevant features of the C++ language are thus introduced with direct relation to the tasks in image and speech processing. "Die Behandlung der C++-Konstukte ist wirklich anwendungsnah." Prof. Dr. Michael Schenke, FH Merseburg "// sehr umfassend - anschaulich, klar, gut nachvollziehbar." Prof. Dr.-Ing. Hans Peter Kölzer, HAW Hamburg "Dieses Buch werde ich meinen Studenten empfehlen, weil es einen sehr anschaulichen und motivierenden Einstieg in die Mustererkennung bietet." Prof. Dr. Hans-Peter Weber, FH Darmstadt Concerning 3rd edition: "This book is a beautifully arranged marriage of state-of-the-art pattern recognition theory and of programming theory and practice. The elegant and thorough treatment of modern aspects of speech and video processing and interpretation springs to life through a multitude of well-designed case studies and concrete examples." Carlo Tomasi, Prof. of Computer Science, Duke University, USA "This book is a must for learners of practical image processing. The examples are well explained and cover the needs of a graduate image processing or pattern recognition course." Laszlo Csink, Prof. of Computer Science, Budapest Polytechnic John von Neumann Faculty of Informatics, Hungary "I am not aware of a book comparable to this one which gives an excellent combination of an account of relevant topics in pattern recognition as well as of techniques for implementing the equations and algorithms in C++. Therefore, the book is invaluable both to students starting in the field and and to practitioners needing a special algorithm and its implementation." H. Niemann, Prof. of Computer Science, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany "// this book has been the perfect source for my students and me. Not only that the reader is elegantly and in a straightforward manner guided to the central points of the theory, but in parallel the authors also make it transparent how to implement the algorithms resulting from the theory." Volkmar Welker, Prof. of Discrete Mathematics, University of Marburg, Germany Bildverarbeitung C++ Programmiersprache Efficient Algorithms Informatik EDV Image Processing Inheritance Mustererkennung Pattern Analysis pattern recognition Program Design programming software development Speech processing Spracherkennung statistical pattern recognition Informatik Grafik Design Digitale Bildverarbeitung Mathematik Programmiersprachen Programmierwerkzeuge Studium Künstliche Intelligenz Robotik In englischer Sprache. 357 pages. 20,3 x 15,2 x 2,5 cm.

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Book Hardcover. Zustand: As New. No Jacket. 1st Edition. Springer, 2007. 1st Edition . As New/No Jacket. Book still in original shrink-wrap.

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