001439553 000__ 07554cam\a2200661\i\4500 001439553 001__ 1439553 001439553 003__ OCoLC 001439553 005__ 20230309004434.0 001439553 006__ m\\\\\o\\d\\\\\\\\ 001439553 007__ cr\cn\nnnunnun 001439553 008__ 210910s2021\\\\sz\a\\\\o\\\\\101\0\eng\d 001439553 020__ $$a9783030863371$$q(electronic bk.) 001439553 020__ $$a3030863379$$q(electronic bk.) 001439553 020__ $$z9783030863364 001439553 0247_ $$a10.1007/978-3-030-86337-1$$2doi 001439553 035__ $$aSP(OCoLC)1267709672 001439553 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ 001439553 049__ $$aISEA 001439553 050_4 $$aTA1630$$b.I58 2021 001439553 08204 $$a006.4/2$$223 001439553 1112_ $$aInternational Conference on Document Analysis and Recognition$$n(16th :$$d2021 :$$cLausanne, Switzerland ; Online) 001439553 24510 $$aDocument analysis and recognition - ICDAR 2021 :$$b16th international conference, Lausanne, Switzerland, September 5-10, 2021 : proceedings.$$nPart IV /$$cJosep Lladós, Daniel Lopresti, Seiichi Uchida (eds.). 001439553 24630 $$aICDAR 2021 001439553 264_1 $$aCham :$$bSpringer,$$c[2021] 001439553 264_4 $$c©2021 001439553 300__ $$a1 online resource (xx, 799 pages) :$$billustrations (chiefly color) 001439553 336__ $$atext$$btxt$$2rdacontent 001439553 337__ $$acomputer$$bc$$2rdamedia 001439553 338__ $$aonline resource$$bcr$$2rdacarrier 001439553 4901_ $$aLecture notes in computer science ;$$v12824 001439553 4901_ $$aLNCS sublibrary: SL6 - Image processing, computer vision, pattern recognition, and graphics 001439553 500__ $$aInternational conference proceedings. 001439553 500__ $$aIncludes author index. 001439553 5050_ $$aScene Text Detection and Recognition -- HRRegionNet: Chinese Character Segmentation in Historical Documents with Regional Awareness -- Fast Text v. Non-text Classification of Images -- Mask Scene Text Recognizer -- Rotated Box Is Back: An Accurate Box Proposal Network for Scene Text Detection -- Heterogeneous Network Based Semi-supervised Learning For Scene Text Recognition -- Scene Text Detection with Scribble Line -- EEM: An End-to-end Evaluation Metric for Scene Text Detection and Recognition -- SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models -- Fast Recognition for Multidirectional and Multi-Type License Plates with 2D Spatial Attention -- A Multi-level Progressive Rectification Mechanism for Irregular Scene Text Recognition -- Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognition -- FEDS -- Filtered Edit Distance Surrogate -- Bidirectional Regression for Arbitrary-Shaped Text Detection -- Document Classification -- VML-HP: Hebrew paleography dataset -- Open Set Authorship Attribution toward Demystifying Victorian Periodicals -- A More Effective Sentence-Wise Text Segmentation Approach using BERT -- Data Augmentation for Writer Identification Using a Cognitive Inspired Model -- Key-guided Identity Document Classification Method by Graph Attention Network -- Document Image Quality Assessment via Explicit Blur and Text Size Estimation -- Analyzing the potential of Zero-Shot Recognition for Document Image Classification -- Gender Detection Based on Spatial Pyramid Matching -- EDNets: Deep Feature Learning for Document Image Classification based on Multi-view Encoder-Decoder Neural Networks -- Fast End-to-end Deep Learning Identity Document Detection, Classification and Cropping -- Gold-Standard Benchmarks and Data Sets -- Image Collation: Matching illustrations in manuscripts -- Revisiting the Coco Panoptic Metric to Enable Visual and Qualitative Analysis of Historical Map Instance Segmentation -- A Large Multi-Target Dataset of Common Bengali Handwritten Graphemes -- GNHK: A Dataset for English Handwriting in the Wild -- Personalizing Handwriting Recognition Systems with Limited User-Specific Samples -- An Efficient Local Word Augment Approach for Mongolian Handwritten Script Recognition -- IIIT-INDIC-HW-WORDS: A Dataset for Indic Handwritten Text Recognition -- Historical Document Analysis -- AT-ST: Self-Training Adaptation Strategy for OCR in Domains with Limited Transcriptions -- TS-Net: OCR Trained to Switch Between Text Transcription Styles -- Handwriting Recognition with Novelty -- Vectorization of Historical Maps Using Deep Edge Filtering and Closed Shape Extraction -- Data Augmentation Based on CycleGAN for Improving Woodblock-printing Mongolian Words Recognition -- SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization -- Handwriting Recognition -- Recognizing Handwritten Chinese Texts with Insertion and Swapping Using A Structural Attention Network -- Strikethrough Removal From Handwritten Words Using CycleGANs -- Iterative Weighted Transductive Learning for Handwriting Recognition -- Competition Reports -- ICDAR 2021 Competition on Scientific Literature Parsing -- ICDAR 2021 Competition on Historical Document Classification -- ICDAR 2021 Competition on Document Visual Question Answering -- ICDAR 2021 Competition on Scene Video Text Spotting -- ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment -- ICDAR 2021 Competition on Components Segmentation Task of Document Photos -- ICDAR 2021 Competition on Historical Map Segmentation -- ICDAR 2021 Competition on Time-Quality Document Image Binarization -- ICDAR 2021 Competition on On-Line Signature Verification -- ICDAR 2021 Competition on Script Identification in the Wild -- ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX -- ICDAR 2021 Competition on Multimodal Emotion Recognition on Comics Scenes -- ICDAR 2021 Competition on Mathematical Formula Detection. 001439553 506__ $$aAccess limited to authorized users. 001439553 520__ $$aThis four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports. The papers are organized into the following topical sections: scene text detection and recognition, document classification, gold-standard benchmarks and data sets, historical document analysis, and handwriting recognition. In addition, the volume contains results of 13 scientific competitions held during ICDAR 2021. 001439553 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 10, 2021). 001439553 650_0 $$aOptical data processing$$vCongresses. 001439553 650_0 $$aDocument imaging systems$$vCongresses. 001439553 650_0 $$aText processing (Computer science)$$vCongresses. 001439553 650_6 $$aTraitement optique de l'information$$vCongrès. 001439553 650_6 $$aGestion électronique de documents$$vCongrès. 001439553 650_6 $$aTraitement de texte$$vCongrès. 001439553 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772 001439553 655_7 $$aConference papers and proceedings.$$2lcgft 001439553 655_7 $$aActes de congrès.$$2rvmgf 001439553 655_0 $$aElectronic books. 001439553 7001_ $$aLladós, Josep,$$d1968-$$eeditor. 001439553 7001_ $$aLopresti, Daniel Philip,$$eeditor. 001439553 7001_ $$aUchida, Seiichi,$$eeditor. 001439553 830_0 $$aLecture notes in computer science ;$$v12824. 001439553 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics. 001439553 852__ $$bebk 001439553 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-86337-1$$zOnline Access$$91397441.1 001439553 909CO $$ooai:library.usi.edu:1439553$$pGLOBAL_SET 001439553 980__ $$aBIB 001439553 980__ $$aEBOOK 001439553 982__ $$aEbook 001439553 983__ $$aOnline 001439553 994__ $$a92$$bISE