02905oam 2200481 450 991083003250332120230629234227.01-119-61859-21-119-61857-61-119-61862-2(CKB)4100000011248694(MiAaPQ)EBC6452645(MiAaPQ)EBC6939941(Au-PeEL)EBL6939941(EXLCZ)99410000001124869420210615d2021 uy 0engurcn#|||a|a||txtrdacontentcrdamediacrrdacarrierImage processing dealing with texture /(the late) Maria Petrou, formerly, Imperial College, London, UK ; revising author Sei-ichiro Kamata, Waseda University, Tokyo/Kitakyushu, JapanSecond edition.Hoboken, New Jersey ;Chichester, England :John Wiley & Sons, Incorporated,[2021]©20211 online resource (819 pages) illustrationsPrint version: Petrou, Maria. Image processing Second edition. Hoboken, NJ : Wiley, 2021. 9781119618553 (DLC) 2020028752 9781119618553 Includes bibliographical references and index."Image Processing: Dealing with Textures (2006) has been, for some time, the only book focusing solely on image texture analysis theory, and remains the classic advanced text on the topic. This welcome update brings the original into the 21st century, without abandoning the foundational essentials of this milestone work. Revising author Sei-ichiro Kamata has provided a sympathetic and respectful revision of the late Maria Petrou's original, and delivers an extensive and exhaustive reappraisal worthy of her memory. Chapters receiving complete overhauls include Fractals and Multifractals, Image Statistics, Texture Repair, Local phase Features, Dual tree Complex Wavelet Transform, Ridgelets and Curvelets, and Deep Texture Features. Image Processing: Dealing with Textures 2nd Edition continues the analysis of texture in digital images which are essential to a range of applications in areas as diverse as robotics, defense, medicine and the geo-sciences. It is structured around a series of questions and answers, enabling readers to easily locate information on specific problems. Readers must have some elementary knowledge of Image Processing and Mathematics; there are more advanced topics in this new edition"--Provided by publisher.Image processingDigital techniquesImage processingDigital techniques.617.6/342621.367Petrou Maria45889Kamata Sei-ichiroebrary, Inc.MiAaPQMiAaPQUtOrBLWBOOK9910830032503321Image processing4124830UNINA05852nam 2200817Ia 450 991082365000332120200520144314.09786612186028978128218602612821860279780470488065047048806997804704880580470488050(CKB)1000000000773803(EBL)448827(SSID)ssj0000112215(PQKBManifestationID)11128382(PQKBTitleCode)TC0000112215(PQKBWorkID)10087004(PQKB)11715927(Au-PeEL)EBL448827(CaPaEBR)ebr10315655(CaONFJC)MIL218602(FINmELB)ELB178395(OCoLC)441892308(MiAaPQ)EBC448827(Perlego)2752571(EXLCZ)99100000000077380320090226d2009 uy 0engur|n|---|||||txtccrBiomolecular networks methods and applications in systems biology /Luonan Chen, Rui-Sheng Wang, Xiang-Sun Zhang1st ed.Hoboken, NJ Wileyc20091 online resource (420 p.)Wiley series on bioinformaticsDescription based upon print version of record.9780470243732 0470243732 Includes bibliographical references and index.BIOMOLECULAR NETWORKS; CONTENTS; PREFACE; ACKNOWLEDGMENTS; LIST OF ILLUSTRATIONS; ACRONYMS; 1 Introduction; 1.1 Basic Concepts in Molecular Biology; 1.1.1 Genomes, Genes, and DNA Replication Process; 1.1.2 Transcription Process for RNA Synthesis; 1.1.3 Translation Process for Protein Synthesis; 1.2 Biomolecular Networks in Cells; 1.3 Network Systems Biology; 1.4 About This Book; I GENE NETWORKS; 2 Transcription Regulation: Networks and Models; 2.1 Transcription Regulation and Gene Expression; 2.1.1 Transcription and Gene Regulation; 2.1.2 Microarray Experiments and Databases2.1.3 ChIP-Chip Technology and Transcription Factor Databases2.2 Networks in Transcription Regulation; 2.3 Nonlinear Models Based on Biochemical Reactions; 2.4 Integrated Models for Regulatory Networks; 2.5 Summary; 3 Reconstruction of Gene Regulatory Networks; 3.1 Mathematical Models of Gene Regulatory Network; 3.1.1 Boolean Networks; 3.1.2 Bayesian Networks; 3.1.3 Markov Networks; 3.1.4 Differential Equations; 3.2 Reconstructing Gene Regulatory Networks; 3.2.1 Singular Value Decomposition; 3.2.2 Model-Based Optimization; 3.3 Inferring Gene Networks from Multiple Datasets3.3.1 General Solutions and a Particular Solution of Network Structures for Multiple Datasets3.3.2 Decomposition Algorithm; 3.3.3 Numerical Validation; 3.4 Gene Network-Based Drug Target Identification; 3.4.1 Network Identification Methods; 3.4.2 Linear Programming Framework; 3.5 Summary; 4 Inference of Transcriptional Regulatory Networks; 4.1 Predicting TF Binding Sites and Promoters; 4.2 Inference of Transcriptional Interactions; 4.2.1 Differential Equation Methods; 4.2.2 Bayesian Approaches; 4.2.3 Data Mining and Other Methods; 4.3 Identifying Combinatorial Regulations of TFs4.4 Inferring Cooperative Regulatory Networks4.4.1 Mathematical Models; 4.4.2 Estimating TF Activity; 4.4.3 Linear Programming Models; 4.4.4 Numerical Validation; 4.5 Prediction of Transcription Factor Activity; 4.5.1 Matrix Factorization; 4.5.2 Nonlinear Models; 4.6 Summary; II PROTEIN INTERACTION NETWORKS; 5 Prediction of Protein-Protein Interactions; 5.1 Experimental Protein-Protein Interactions; 5.2 Prediction of Protein-Protein Interactions; 5.2.1 Association Methods; 5.2.2 Maximum-Likelihood Estimation; 5.2.3 Deterministic Optimization Approaches5.3 Protein Interaction Prediction Based on Multidomain Pairs5.3.1 Cooperative Domains, Strongly Cooperative Domains, Superdomains; 5.3.2 Inference of Multidomain Interactions; 5.3.3 Numerical Validation; 5.3.4 Reconstructing Complexes by Multidomain Interactions; 5.4 Domain Interaction Prediction Methods; 5.4.1 Statistical Method; 5.4.2 Domain Pair Exclusion Analysis; 5.4.3 Parsimony Explanation Approaches; 5.4.4 Integrative Approaches; 5.5 Summary; 6 Topological Structure of Biomolecular Networks; 6.1 Statistical Properties of Biomolecular Networks6.2 Evolution of Protein Interaction NetworksAlternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the imporWiley series on bioinformatics.Molecular biologyData processingComputational biologyBioinformaticsBiological systemsResearchData processingMolecular biologyData processing.Computational biology.Bioinformatics.Biological systemsResearchData processing.572.80285Chen Luonan1962-1641968Wang Rui-Sheng1641969Zhang Xiang-Sun1943-1641970MiAaPQMiAaPQMiAaPQBOOK9910823650003321Biomolecular networks3986413UNINA