LEADER 02799nam 2200661 a 450 001 9910456509903321 005 20200520144314.0 010 $a1-283-14641-X 010 $a9786613146410 010 $a0-8032-3601-8 035 $a(CKB)2550000000037406 035 $a(EBL)725902 035 $a(OCoLC)733040372 035 $a(SSID)ssj0000538647 035 $a(PQKBManifestationID)11327077 035 $a(PQKBTitleCode)TC0000538647 035 $a(PQKBWorkID)10559953 035 $a(PQKB)11108784 035 $a(MiAaPQ)EBC725902 035 $a(MdBmJHUP)muse3722 035 $a(Au-PeEL)EBL725902 035 $a(CaPaEBR)ebr10476206 035 $a(CaONFJC)MIL314641 035 $a(EXLCZ)992550000000037406 100 $a20100923d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aLiving with Koryak traditions$b[electronic resource] $eplaying with culture in Siberia /$fAlexander D. King 210 $aLincoln $cUniversity of Nebraska Press$d2011 215 $a1 online resource (348 p.) 300 $aDescription based upon print version of record. 311 $a0-8032-3509-7 320 $aIncludes bibliographical references and index. 327 $aTitle Page; Copyright Page; Table of Contents; List of Illustrations; Preface; Introduction: A Semiotics of Koryak Culture; 1. Discovering Koryak Culture through History; 2. Genuine and Spurious Culture in Kamchatka; 3. Dancing in the Koryak House of Culture; 4. The Culture of Schools and Museums; 5. "This Is Not My Language!": Koryak Language in Schools; Conclusion: Koryak Culture and the Future of Tradition; Notes; Glossary; References; Index 330 $aAn examination of the globalization of culture and the invention of tradition, and what it means to modern Koryak people living in post-Soviet Siberia. 606 $aKoryaks$zRussia (Federation)$zKamchatka Peninsula$xHistory 606 $aKoryaks$zRussia (Federation)$zKamchatka Peninsula$xEthnic identity 606 $aKoryaks$xCultural assimilation$zRussia (Federation)$zKamchatka Peninsula 606 $aCulture and globalization$zRussia (Federation)$zKamchatka Peninsula 607 $aKamchatka Peninsula (Russia)$xEthnic relations 607 $aKamchatka Peninsula (Russia)$xSocial life and customs 608 $aElectronic books. 615 0$aKoryaks$xHistory. 615 0$aKoryaks$xEthnic identity. 615 0$aKoryaks$xCultural assimilation 615 0$aCulture and globalization 676 $a305.89/46 700 $aKing$b Alexander David$0946589 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910456509903321 996 $aLiving with Koryak traditions$92138516 997 $aUNINA LEADER 05084nam 22007935 450 001 9910805579603321 005 20251027095400.0 010 $a981-9978-82-3 024 7 $a10.1007/978-981-99-7882-3 035 $a(MiAaPQ)EBC31086060 035 $a(Au-PeEL)EBL31086060 035 $a(DE-He213)978-981-99-7882-3 035 $a(MiAaPQ)EBC31093863 035 $a(Au-PeEL)EBL31093863 035 $a(CKB)30113006900041 035 $a(EXLCZ)9930113006900041 100 $a20240124d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Image Classification $eFrom Designed Models to End-to-End Learning /$fby Klaus D. Toennies 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (297 pages) 311 08$aPrint version: Toennies, Klaus D. An Introduction to Image Classification Singapore : Springer,c2024 9789819978816 327 $aChapter 1. Image Classification ? A Computer Vision Task -- Chapter 2. Image Features ? Extraction and Categories -- Chapter 3. Feature Reduction -- Chapter 4. Bayesian Image Classification in Feature Space -- Chapter 5. Distance-based Classifiers -- Chapter 6. Decision Boundaries in Feature Space -- Chapter 7. Multi-layer Perceptron for Image Classification -- Chapter 8. Feature Extraction by Convolutional Neural Network -- Chapter 9. Network Set-up for Image Classification -- Chapter 10. Basic Network Training for Image Classification -- Chapter 11. Dealing with Training Deficiencies -- Chapter 12. Learning Effects and Network Decisions. 330 $aImage classification is a critical component in computer vision tasks and has numerous applications. Traditional methods for image classification involve feature extraction and classification in feature space. Current state-of-the-art methods utilize end-to-end learning with deep neural networks, where feature extraction and classification are integrated into the model. Understanding traditional image classification is important because many of its design concepts directly correspond to components of a neural network. This knowledge can help demystify the behavior of these networks, which may seem opaque at first sight. The book starts from introducing methods for model-driven feature extraction and classification, including basic computer vision techniques for extracting high-level semantics from images. A brief overview of probabilistic classification with generative and discriminative classifiers is then provided. Next, neural networks are presented as a means to learn a classification model directly from labeled sample images, with individual components of the network discussed. The relationships between network components and those of a traditional designed model are explored, and different concepts for regularizing model training are explained. Finally, various methods for analyzing what a network has learned are covered in the closing section of the book. The topic of image classification is presented as a thoroughly curated sequence of steps that gradually increase understanding of the working of a fully trainable classifier. Practical exercises in Python/Keras/Tensorflow have been designed to allow for experimental exploration of these concepts. In each chapter, suitable functions from Python modules are briefly introduced to provide students with the necessary tools to conduct these experiments. 606 $aComputer vision 606 $aMachine learning 606 $aPattern recognition systems 606 $aBiometric identification 606 $aArtificial intelligence$xData processing 606 $aComputer Vision 606 $aMachine Learning 606 $aAutomated Pattern Recognition 606 $aBiometrics 606 $aData Science 606 $aVisiķ per ordinador$2thub 606 $aAprenentatge automātic$2thub 606 $aReconeixement de formes (Informātica)$2thub 606 $aIdentificaciķ biomčtrica$2thub 606 $aProcessament de dades$2thub 608 $aLlibres electrōnics$2thub 615 0$aComputer vision. 615 0$aMachine learning. 615 0$aPattern recognition systems. 615 0$aBiometric identification. 615 0$aArtificial intelligence$xData processing. 615 14$aComputer Vision. 615 24$aMachine Learning. 615 24$aAutomated Pattern Recognition. 615 24$aBiometrics. 615 24$aData Science. 615 7$aVisiķ per ordinador 615 7$aAprenentatge automātic 615 7$aReconeixement de formes (Informātica) 615 7$aIdentificaciķ biomčtrica 615 7$aProcessament de dades 676 $a006.37 700 $aToennies$b Klaus D$01060341 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910805579603321 996 $aAn Introduction to Image Classification$93882665 997 $aUNINA