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001440799 001__ 1440799
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001440799 020__ $$a9783030891312$$q(electronic bk.)
001440799 020__ $$a3030891313$$q(electronic bk.)
001440799 020__ $$z9783030891305
001440799 0247_ $$a10.1007/978-3-030-89131-2$$2doi
001440799 035__ $$aSP(OCoLC)1283844064
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001440799 049__ $$aISEA
001440799 050_4 $$aTA1637$$b.I58 2021
001440799 08204 $$a006.6$$223
001440799 1112_ $$aInternational Conference on Computer Analysis of Images and Patterns$$n(19th :$$d2021 :$$cOnline)
001440799 24510 $$aComputer analysis of images and patterns :$$b19th international conference, CAIP 2021, virtual event, September 28-30, 2021 : proceedings.$$nPart II /$$cNicolas Tsapatsoulis, Andreas Panayides, Theo Theocharides, Andreas Lanitis, Constantinos Pattichis, Mario Vento (eds.).
001440799 24630 $$aCAIP 2021
001440799 264_1 $$aCham :$$bSpringer,$$c[2021]
001440799 264_4 $$c©2021
001440799 300__ $$a1 online resource (457 pages) :$$billustrations (chiefly color)
001440799 336__ $$atext$$btxt$$2rdacontent
001440799 337__ $$acomputer$$bc$$2rdamedia
001440799 338__ $$aonline resource$$bcr$$2rdacarrier
001440799 347__ $$atext file
001440799 347__ $$bPDF
001440799 4901_ $$aLecture notes in computer science ;$$v13053
001440799 4901_ $$aLNCS sublibrary: SL6 - Image processing, computer vision, pattern recognition, and graphics
001440799 500__ $$aInternational conference proceedings.
001440799 500__ $$aIncludes author index.
001440799 5050_ $$aIntro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Machine Learning -- Deep Learning Based Automated Vickers Hardness Measurement -- 1 Introduction and Related Work -- 2 Methodology -- 2.1 Indentation Segmentation Using Convolutional Neural Network -- 2.2 Edge Extraction and Initial Indention Vertex Position Estimation -- 2.3 Precision Improvement -- 3 Experimental Framework -- 4 Experiments and Results -- 5 Conclusion -- References -- ElasticHash: Semantic Image Similarity Search by Deep Hashing with Elasticsearch -- 1 Introduction -- 2 Related Work
001440799 5058_ $$a3 ElasticHash -- 3.1 Deep Hashing Model -- 3.2 Integration into ES -- 4 Experimental Evaluation -- 4.1 Results -- 5 Conclusion -- References -- Land Use Change Detection Using Deep Siamese Neural Networks and Weakly Supervised Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Multi Filter Multi-scale Deep Convolutional Neural Network -- 3.2 Siamese Neural Network -- 3.3 Generation of Change Detection Maps -- 4 Experimental Setup -- 4.1 Datasets' Description -- 4.2 Model Adaptation and Parameter Setting -- 5 Results -- 5.1 Ablation Analysis of the Proposed Model -- 6 Conclusions
001440799 5058_ $$a5.3 Results -- 6 Conclusions -- References -- Unsupervised Recognition of the Logical Structure of Business Documents Based on Spatial Relationships -- 1 Introduction and Context -- 2 State of the Art -- 3 Proposal -- 4 Spatial Contexts -- 4.1 Metadata to Captions Spatial Context (MCSC) -- 4.2 Metadata to Metadata Spatial Context (MMSC) -- 5 Voting and Detection Stages -- 5.1 Voting by Using Metadata Position -- 5.2 Voting by Using the Metadata to Captions Spatial Context -- 5.3 Voting by Using the Metadata Format -- 5.4 Voting by Using the MMSC -- 5.5 Detection Stage -- 6 Results -- 7 Conclusion
001440799 506__ $$aAccess limited to authorized users.
001440799 520__ $$aThe two volume set LNCS 13052 and 13053 constitutes the refereed proceedings of the 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, held virtually, in September 2021. The 87 papers presented were carefully reviewed and selected from 129 submissions. The papers are organized in the following topical sections across the 2 volumes: 3D vision, biomedical image and pattern analysis; machine learning; feature extractions; object recognition; face and gesture, guess the age contest, biometrics, cryptography and security; and segmentation and image restoration.
001440799 588__ $$aDescription based on print version record.
001440799 650_0 $$aImage processing$$xDigital techniques$$vCongresses.
001440799 650_0 $$aComputer vision$$vCongresses.
001440799 650_0 $$aPattern recognition systems$$vCongresses.
001440799 650_6 $$aTraitement d'images$$xTechniques numériques$$vCongrès.
001440799 650_6 $$aVision par ordinateur$$vCongrès.
001440799 650_6 $$aReconnaissance des formes (Informatique)$$vCongrès.
001440799 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001440799 655_7 $$aConference papers and proceedings.$$2lcgft
001440799 655_7 $$aActes de congrès.$$2rvmgf
001440799 655_0 $$aElectronic books.
001440799 7001_ $$aTsapatsoulis, Nicolas,$$d1969-$$eeditor.
001440799 7001_ $$aPanayides, Andreas,$$eeditor.
001440799 7001_ $$aTheocharides, Theo,$$eeditor.
001440799 7001_ $$aLanitis, Andreas,$$eeditor.
001440799 7001_ $$aPattichis, Constantinos S.,$$eeditor.
001440799 7001_ $$aVento, Mario,$$d1960-$$eeditor.
001440799 77608 $$iPrint version:$$aTsapatsoulis, Nicolas.$$tComputer Analysis of Images and Patterns.$$dCham : Springer International Publishing AG, ©2021$$z9783030891305
001440799 830_0 $$aLecture notes in computer science ;$$v13053.
001440799 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
001440799 852__ $$bebk
001440799 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-89131-2$$zOnline Access$$91397441.1
001440799 909CO $$ooai:library.usi.edu:1440799$$pGLOBAL_SET
001440799 980__ $$aBIB
001440799 980__ $$aEBOOK
001440799 982__ $$aEbook
001440799 983__ $$aOnline
001440799 994__ $$a92$$bISE