Document Analysis and Recognition - ICDAR 2023

Table of Contents

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   Book Overview
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   Chapter 1 Transductive Learning for Near-Duplicate Image Detection in Scanned Photo Collections
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   Chapter 2 Incremental Learning and Ambiguity Rejection for Document Classification
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   Chapter 3 EEBO-Verse: Sifting for Poetry in Large Early Modern Corpora Using Visual Features
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   Chapter 4 A Graphical Approach to Document Layout Analysis
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   Chapter 5 Gaussian Kernels Based Network for Multiple License Plate Number Detection in Day-Night Images
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   Chapter 6 Ensuring an Error-Free Transcription on a Full Engineering Tags Dataset Through Unsupervised Post-OCR Methods
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   Chapter 7 Unraveling Confidence: Examining Confidence Scores as Proxy for OCR Quality
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   Chapter 8 Optimizing the Performance of Text Classification Models by Improving the Isotropy of the Embeddings Using a Joint Loss Function
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    Chapter 9 FTDNet: Joint Semantic Learning for Scene Text Detection in Adverse Weather Conditions
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    Chapter 10 DocParser: End-to-end OCR-Free Information Extraction from Visually Rich Documents
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    Chapter 11 MUGS: A Multiple Granularity Semi-supervised Method for Text Recognition
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    Chapter 12 A Hybrid Approach to Document Layout Analysis for Heterogeneous Document Images
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    Chapter 13 ColDBin: Cold Diffusion for Document Image Binarization
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    Chapter 14 You Only Look for a Symbol Once: An Object Detector for Symbols and Regions in Documents
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    Chapter 15 SAN: Structure-Aware Network for Complex and Long-Tailed Chinese Text Recognition
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    Chapter 16 TACTFUL: A Framework for Targeted Active Learning for Document Analysis
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    Chapter 17 End-to-End Multi-line License Plate Recognition with Cascaded Perception
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    Chapter 18 Evaluating Adversarial Robustness on Document Image Classification
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    Chapter 19 UTRNet: High-Resolution Urdu Text Recognition in Printed Documents
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    Chapter 20 Layout Analysis of Historical Document Images Using a Light Fully Convolutional Network
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    Chapter 21 Combining OCR Models for Reading Early Modern Books
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    Chapter 22 Detecting Text on Historical Maps by Selecting Best Candidates of Deep Neural Networks Output
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    Chapter 23 Aligning Benchmark Datasets for Table Structure Recognition
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    Chapter 24 LineFormer: Line Chart Data Extraction Using Instance Segmentation
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    Chapter 25 Line-of-Sight with Graph Attention Parser (LGAP) for Math Formulas
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    Chapter 26 PyramidTabNet: Transformer-Based Table Recognition in Image-Based Documents
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    Chapter 27 Line Graphics Digitization: A Step Towards Full Automation
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    Chapter 28 Linear Object Detection in Document Images Using Multiple Object Tracking
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    Chapter 29 TRACE: Table Reconstruction Aligned to Corner and Edges
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    Chapter 30 Contour Completion by Transformers and Its Application to Vector Font Data
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    Chapter 31 Towards Making Flowchart Images Machine Interpretable
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    Chapter 32 Formerge: Recover Spanning Cells in Complex Table Structure Using Transformer Network
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    Chapter 33 GriTS: Grid Table Similarity Metric for Table Structure Recognition