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001435172 001__ 1435172
001435172 003__ OCoLC
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001435172 019__ $$a1242465222$$a1249945119
001435172 020__ $$a9783030579074$$q(electronic bk.)
001435172 020__ $$a3030579077$$q(electronic bk.)
001435172 020__ $$z9783030579067
001435172 020__ $$z3030579069
001435172 0247_ $$a10.1007/978-3-030-57907-4$$2doi
001435172 035__ $$aSP(OCoLC)1243541055
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001435172 049__ $$aISEA
001435172 050_4 $$aCC135
001435172 08204 $$a363.6/9$$223
001435172 08204 $$a004$$223
001435172 24500 $$aDigital techniques for heritage presentation and preservation /$$cJayanta Mukhopadhyay, Indu Sreedevi, Bhabatosh Chanda, Santanu Chaudhury, Vinay P. Namboodiri, editors.
001435172 260__ $$aCham :$$bSpringer,$$c2021.
001435172 300__ $$a1 online resource (275 pages)
001435172 336__ $$atext$$btxt$$2rdacontent
001435172 337__ $$acomputer$$bc$$2rdamedia
001435172 338__ $$aonline resource$$bcr$$2rdacarrier
001435172 500__ $$a3.1 Training Data Generation.
001435172 5058_ $$a3.4.2 Selection of Essential Keypoints (for Word Spotting) -- 3.4.3 Spotting Zones -- 3.4.4 Ranking of Spotted Zone -- 4 Experimental Results -- 4.1 Datasets and Ground Truth for Word Spotting -- 4.2 Datasets and Ground Truth for Figure Spotting -- 4.3 Determining the Value of -- 4.4 Selecting the Value of k -- 4.5 Results and Analysis -- 5 Conclusion -- References -- Part II Restoration and Reconstruction of Digital Heritage Artifacts -- Text Extraction and Restoration of Old Handwritten Documents -- 1 Introduction -- 1.1 Dataset -- 2 Literature Review -- 3 Proposed Method
001435172 5050_ $$aIntro -- Preface -- Acknowledgments -- Organization -- Contents -- Part I Classification and Retrieval of Heritage Data -- Introduction to Heritages and Heritage Management: A Preview -- 1 Introduction -- 2 Classification of Heritages -- 3 Mapping of World Heritages -- 4 Digital Heritage -- 5 Public, Classified, and Personal Digital Heritage -- 6 Science and Digital Heritages -- 7 Computer-Based Processing of Digital Heritage -- 8 Threats to Digital Heritage -- 9 Motivation for Digital Heritage -- References -- Language-Based Text Categorization: A Survey -- 1 Introduction
001435172 5058_ $$a1.1 Monolingual Text Categorization -- 1.2 Multilingual Text Classification -- 1.2.1 Automatic Language Identification -- 1.2.2 Preprocessing -- 1.2.3 Feature Extraction -- 1.2.4 Learning/Training Phase -- 1.3 Language and Document Models -- 1.4 Applications of Language Identification -- 1.5 Supervised Learning Methods for Text Categorization -- 1.5.1 Naïve Bayes Method -- 1.5.2 K-Nearest Neighbor -- 1.5.3 Support Vector Machine -- 1.5.4 Decision Tree Classifier -- 1.5.5 Neural Networks -- 1.5.6 Performance Measures -- 2 Related Work -- 2.1 Categorization of Monolingual Text Documents
001435172 5058_ $$a2.2 Multilingual Text Categorization -- 2.3 Way Forward -- 3 Conclusion -- References -- Classification of Yoga Asanas from a Single Image by Learning the 3D View of Human Poses -- 1 Introduction -- 2 Related Work -- 2.1 Multiple-View 3D Human Pose Estimation -- 2.2 Single-View 3D Human Pose Estimation -- 3 Proposed Method -- 3.1 3D Pose Estimation -- 3.2 Classification of Yoga Asanas Based on Poses -- 4 Dataset and Experiments -- 5 Results -- 6 Observations/Conclusion -- References -- IHIRD: A Data Set for Indian Heritage Image Retrieval -- 1 Introduction -- 2 Description of the Data Set
001435172 5058_ $$a3 Data Set Preparation -- 4 Development of Content-Based Image Retrieval System -- 4.1 Selection of Feature Descriptor and Distance Function -- 4.2 Indexing of the Image Database -- 4.3 Ontology-Driven Content-Based Image Search -- 5 Experimental Results -- 6 Conclusion -- References -- Object Spotting in Historical Documents -- 1 Introduction -- 2 Related Work -- 2.1 Word Spotting -- 2.2 Figure Spotting -- 3 Proposed Method -- 3.1 Keypoint Detection -- 3.2 Keypoint Descriptor -- 3.3 Estimation of Laplace-Beltrami Operator -- 3.4 Object Spotting -- 3.4.1 Candidate Keypoint Selection
001435172 506__ $$aAccess limited to authorized users.
001435172 520__ $$aThis book describes various new computer based approaches which can be exploited for the (digital) reconstruction, recognition, restoration, presentation and classification of digital heritage. They are based on applications of virtual reality, augmented reality and artificial intelligence, to be used for storing and retrieving of historical artifacts, digital reconstruction, or virtual viewing.
001435172 588__ $$aDescription based on print version record.
001435172 650_0 $$aHistoric preservation$$xTechnological innovations.
001435172 650_0 $$aCultural property$$xProtection$$xTechnological innovations.
001435172 650_6 $$aPréservation historique$$xInnovations.
001435172 655_0 $$aElectronic books.
001435172 7001_ $$aMukhopadhyay, Jayanta$$c(College teacher)
001435172 7001_ $$aSreedevi, Indu.
001435172 7001_ $$aChanda, B.$$q(Bhabatosh)
001435172 7001_ $$aChaudhury, Santanu.
001435172 7001_ $$aNamboodiri, Vinay P.
001435172 77608 $$iPrint version:$$aMukhopadhyay, Jayanta.$$tDigital Techniques for Heritage Presentation and Preservation.$$dCham : Springer International Publishing AG, ©2021$$z9783030579067
001435172 852__ $$bebk
001435172 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-57907-4$$zOnline Access$$91397441.1
001435172 909CO $$ooai:library.usi.edu:1435172$$pGLOBAL_SET
001435172 980__ $$aBIB
001435172 980__ $$aEBOOK
001435172 982__ $$aEbook
001435172 983__ $$aOnline
001435172 994__ $$a92$$bISE