LEADER 01378nam a2200301 i 4500 001 991001487449707536 008 060217s2001 it a b 001 0 ita d 020 $a8870786870 035 $ab13380102-39ule_inst 040 $aDi.S.Te.B.A.$beng 082 0 $a572$222 245 00$aMetodologia biochimica :$ble bioscienze e le biotecnologie in laboratorio /$ca cura di Keith Wilson e John Walker 250 $aNuova ed. italiana /$ba cura di Mirella S. Pilone e Loredano Pollegioni 260 $aMilano :$bRaffaello Cortina Ed.,$c[2001] 300 $axx, 778 p. :$bill. ;$c26 cm 500 $aOrig. Tit.: Principles and Tecniques of Practical Biochemistry. - 5th. ed. - Cambridge : Cambridge Univ. Press, 2000 500 $aTranslation of Laura Cortesi, Maurizio Mattioli, Maria Zambrotta 700 1 $aWilson, Keith 700 1 $aWalker, John 700 1 $aPilone, Mirella S. 700 1 $aPollegioni, Loredano 907 $a.b13380102$b13-12-06$c17-02-06 912 $a991001487449707536 945 $aLE003 572 WIL01.02 C.1 (2001)$g1$i2003000049732$lle003$op$pE98.13$q-$rl$s- $t0$u25$v0$w25$x0$y.i14223181$z13-04-06 945 $aLE003 572 WIL01.02 C.2 (2001)$g2$i2003000049749$lle003$op$pE98.13$q-$rl$s- $t0$u61$v0$w61$x0$y.i1422317x$z13-04-06 996 $aMetodologia biochimica$975540 997 $aUNISALENTO 998 $ale003$b17-02-06$cm$da $e-$fita$git $h0$i0 LEADER 04640nam 22005415 450 001 9910337855003321 005 20200705064059.0 010 $a3-030-13773-2 024 7 $a10.1007/978-3-030-13773-1 035 $a(CKB)4100000008409612 035 $a(DE-He213)978-3-030-13773-1 035 $a(MiAaPQ)EBC5923548 035 $a(PPN)24493097X 035 $a(EXLCZ)994100000008409612 100 $a20190605d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aImage Texture Analysis $eFoundations, Models and Algorithms /$fby Chih-Cheng Hung, Enmin Song, Yihua Lan 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XII, 258 p. 142 illus., 73 illus. in color.) 311 $a3-030-13772-4 320 $aIncludes bibliographical references and index. 327 $aPart I: Existing Models and Algorithms for Image Texture -- Image Texture, Texture Features, and Image Texture Classification and Segmentation -- Texture Features and Image Texture Models -- Algorithms for Image Texture Classification -- Dimensionality Reduction and Sparse Representation -- Part II: The K-Views Models and Algorithms -- Basic Concept and Models of the K-Views -- Using Datagram in the K-Views Model -- Features-Based K-Views Model -- Advanced K-Views Algorithms -- Part III: Deep Machine Learning Models for Image Texture Analysis -- Foundations of Deep Machine Learning in Neural Networks -- Convolutional Neural Networks and Texture Classification. 330 $aThis useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: Provides self-test exercises in every chapter Describes the basics of image texture, texture features, and image texture classification and segmentation Examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification Explains the concepts of dimensionality reduction and sparse representation Discusses view-based approaches to classifying images Introduces the template for the K-views algorithm, as well as a range of variants of this algorithm Reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work. Dr. Chih-Cheng Hung is a Tenured Professor of Computer Science in the College of Computing and Software Engineering at Kennesaw State University, where he serves as the Director of the Center for Machine Vision and Security Research. He also holds the position of YinDu Scholar at Anyang Normal University, China. Dr. Enmin Song is a Professor and Director of the Department of Computer Science and Application at Huazhong University of Science and Technology, Wuhan, China. Dr. Yihua Lan is an Associate Professor of Computer Science in the School of Computer and Information Technology at Nanyang Normal University, China. 606 $aOptical data processing 606 $aArtificial intelligence 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aOptical data processing. 615 0$aArtificial intelligence. 615 14$aImage Processing and Computer Vision. 615 24$aArtificial Intelligence. 676 $a006.4 676 $a006.37 700 $aHung$b Chih-Cheng$4aut$4http://id.loc.gov/vocabulary/relators/aut$0997314 702 $aSong$b Enmin$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLan$b Yihua$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337855003321 996 $aImage Texture Analysis$92513500 997 $aUNINA