Verfügbarkeit: Handbook of pattern recognition and computer vision

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Bibliographische Detailangaben
Weitere beteiligte Personen:	Chen, Chi-hau 1937- (HerausgeberIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	New Jersey ; London ; Singapore ; Beijing ; Shanghai ; Hong Kong ; Taipei ; Chennai World Scientific [2016]
Ausgabe:	5th edition
Schlagwörter:	Mustererkennung Maschinelles Sehen Computervision Aufsatzsammlung
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028936431&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028936431&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung:	Literaturangaben
Umfang:	xvi, 565 Seiten Illustrationen, Diagramme (Teilweise farbig)
ISBN:	9789814656528

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Datensatz im Suchindex

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adam_text	CONTENTS Preface to the 5th Edition vii Part 1: Pattern Recognition Methods and Applications 1 Chapter 1.1 Syntactic Pattern Recognition: Paradigm Issues and Open Problems 3 Mariusz Flasinski Chapter 1.2 Deep Discriminative and Generative Models for Speech Pattern Recognition 27 Li Deng and Navdcep Jaiily Chapter 1.3 On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and An Example in Semi-supervised Learning 53 Marco Loog, Jesse H. Krijthe, and Are C. Jensen Chapter 1.4 Information Theoretic Clustering Using a k-Nearest Neighbors-based Divergence Measure 69 Vidar V. Vikjord and Robert Jenssen Chapter 1.5 Pruning Trees in Random Forests for Minimizing Non Detection in Medical Imaging 89 Laurent Heutte, Caroline Petit jean, and Ghesner Desir XIV Contents Chapter 1.6 Recent Advances on Optimum-path Forest for Data Classification: Supervised. Semi-supervised, and Unsupervised Learning 109 Jo do Paulo Papa, Willian Paraguassu Amorim, Alexandre Xavier Falcao, and Jo do Manuel R. S. Tavares Chapter 1.7 On Curvelet-based Texture Features for Pattern Classification 125 Ching- Chung Li and Wen- Ghyi Lin Chapter 1.8 Computer Recognition and Evaluation of Coins 141 Bo-Yuan Feng, Ke Sum Parmida Atighechian, and Ching Y. Suen Chapter 1.9 Supervised and Unsupervised Feature Descriptors for Error-resilient Underwater Live Fish Recognition 159 Meng-Che Chuang, Jenq-Neng Hwang, and Kresimir Williams Chapter 1.10 Model Adaptation for Personalized Music Emotion Recognition 175 Yi-Hsuan Yang. Ju-Chiang Wang, Yu-An Chen, and Homer H. Chen Part 2: Computer Vision and Image Processing 195 Chapter 2.1 Context Assisted Person Identification for Images and Videos 197 Liyan Zhang, Dmitri V. Kalashnikov, and Sharad Mehrotra Chapter 2.2 Statistical Shape Spaces for 3D Data: A Review 217 Alan Brunton. Augusta Salazar. Timo Bolkarl. and Stefame Wuhrer Chapter 2.3 Tracking Without Appearance Descriptors 239 Mehrsan Javan Roshtkhan and Martin D. Levine Contents xv Chapter 2.4 Knowledge Augmented Visual Learning 255 Ziheng Wang and Qiang Ji Chapter 2.5 Graph Edit Distance — Novel Approximation Algorithms 275 Kaspar RAcsen and Horst Bunke Chapter 2.6 Latest Developments of LSTM Neural Networks with Applications of Document Image Analysis 293 Marcus LivnckL Volkmar Frmken, and Muhammad Zeshan Afzal Chapter 2.7 Analyzing Remote Sensing Images with Hierarchial Morphological Ropresei i t aliens 313 Gabride GavaMaro, Marwro Dalla Mum and Jon AtM Bemdiklsson Chapter 2.8 Manifold-based Sparse Representation for Hyperspectral Image Classification 331 Yuan Yarn Tang and, Haoliang Yuan Chapter 2.9 A Review of Texture Classification Methods and Their Applications in Medical Image Analysis of the Brain 351 Rouzheh MaanL Sanjay Kalra. and Yee-Hong Yang Chapter 2.10 3D Tomosynthesis to Detect Breast Cancer 371 Yanbin Lu, Mina Yousefi, John Ellenherger. Richard FL Moore. Daniel B. Koparrts. Adam Krzyzak. mid Cliiiig Y. Suen Part 3: System, Architecture, and Technology 395 Chapter 3.1 Combining Representations for Improved Sketch Recognition 397 Sonya Cates xv Contents Chapter 3.2 Chapter 3.3 Chapter 3.4 Chapter 3.5 Chapter 3.6 Chapter 3.7 Chapter 3.8 Chapter 3.9 Visual Object Recognition with Image Retrieval Sedat Ozer Efficient Identification of Faces in Video Streams Using Low-power Multi-core Devices Donavan Prieur. Eric Granger. Yvon Savaria, and Claude Thibeault Kernel-based Learning for Fault Detection and Identification in Fuel Cell Systems Gabriele Moser, Paola Costamagna, Andrea De Giorgi, Lissy Pellaco. Andrea Trucco, and Sebastiano B. Serpico Outdoor Shadow Modelling and its Applications Lin Gu and Antonio Robles-Kelly Fast Structured Tracker with Improved Motion Model Using Robust Kalman Filter Ivan Bogun and Eraldo Ribeiro Using 3D Vision for Automated Industrial Inspection David J. Michael Vision Challenges in Image-based Barcode Readers Xianju Wang and Xiangyun (Mary) Ye Parallel Pattern Matching Using the Automata Processor Matt Tanner. Matt Grimm, and Harold B. Noyes 415 427 455 473 491 509 521 539 Index 561 HANDBOOK OF PATTERN RECOGNITION AND COMPUTER VISION Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years. Their applications in our daily life, commerce and industry are growing even more rapidly than theoretical advances. Hence, the need for a new handbook in pattern recognition and computer vision every five or six years as envisioned in 1990 is fully justified and valid. The book consists of three parts: (1) Pattern recognition methods and applications; (2) Computer vision and image processing; and (3) Systems, architecture and technology. This book is intended to capture the major developments in pattern recognition and computer vision though it is impossible to cover all topics. The chapters are written by experts from many countries, fully reflecting the strong international research interests in the areas. This fifth edition will complement the previous four editions of the book.
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title	Handbook of pattern recognition and computer vision
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