Document Analysis and Recognition - Icdar 2021 - Bookswagon
Document Analysis and Recognition - Icdar 2021

Document Analysis and Recognition - Icdar 2021


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About the Book

Scene Text Detection and Recognition.- HRRegionNet: Chinese Character Segmentation in Historical Documents with Regional Awareness.- Fast Text v. Non-text Classification of Images.- Mask Scene Text Recognizer.- Rotated Box Is Back: An Accurate Box Proposal Network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 Mathema


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Product Details
  • ISBN-13: 9783030863364
  • Publisher: Springer Nature Switzerland AG
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: 16th International Conference, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part IV
  • Width: 156 mm
  • ISBN-10: 3030863360
  • Publisher Date: 04 Sep 2021
  • Height: 234 mm
  • No of Pages: 820
  • Spine Width: 41 mm
  • Weight: 1178 gr


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