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Document Analysis and Recognition - ICDAR 2023

17th International Conference, San José, CA, USA, August 21–26, 2023, Proceedings, Part I

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Gernot A. Fink

    1. TU Dortmund University, Dortmund, Germany

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  2. Rajiv Jain

    1. Adobe, College Park, USA

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  3. Koichi Kise

    1. Osaka Metropolitan University, Osaka, Japan

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  4. Richard Zanibbi

    1. Rochester Institute of Technology, Rochester, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14187)

Included in the following conference series:

Conference proceedings info: ICDAR 2023.

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About this book

This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, held in San José, CA, USA, in August 2023. The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations.

The papers are organized into the following topical sections: Graphics Recognition, Frontiers in Handwriting Recognition, Document Analysis and Recognition.


Keywords

Table of contents (31 papers)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. Applications 1: Enterprise Documents (Medical, Legal, Finance)

    1. Front Matter

      Pages 1-1
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    2. Multi-stage Fine-Tuning Deep Learning Models Improves Automatic Assessment of the Rey-Osterrieth Complex Figure Test

      • Benjamin Schuster, Florian Kordon, Martin Mayr, Mathias Seuret, Stefanie Jost, Josef Kessler et al.
      Pages 3-19

    3. Structure Diagram Recognition in Financial Announcements

      • Meixuan Qiao, Jun Wang, Junfu **ang, Qiyu Hou, Ruixuan Li
      Pages 20-44

    4. TransDocAnalyser: A Framework for Semi-structured Offline Handwritten Documents Analysis with an Application to Legal Domain

      • Sagar Chakraborty, Gaurav Harit, Saptarshi Ghosh
      Pages 45-62

    5. Context Aware Document Binarization and Its Application to Information Extraction from Structured Documents

      • Ján Koloda, Jue Wang
      Pages 63-78

  3. Frontiers in Handwriting Recognition 1 (Online)

    1. Front Matter

      Pages 79-79
      Download chapter PDF

    2. SET, SORT! A Novel Sub-stroke Level Transformers for Offline Handwriting to Online Conversion

      • Elmokhtar Mohamed Moussa, Thibault Lelore, Harold Mouchère
      Pages 81-97

    3. Character Queries: A Transformer-Based Approach to On-line Handwritten Character Segmentation

      • Michael Jungo, Beat Wolf, Andrii Maksai, Claudiu Musat, Andreas Fischer
      Pages 98-114

  4. Graphics Recognition 3: Math Recognition

    1. Front Matter

      Pages 115-115
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    2. Relative Position Embedding Asymmetric Siamese Network for Offline Handwritten Mathematical Expression recognition

      • Chunyi Wang, Hurunqi Luo, **aqing Rao, Wei Hu, Ning Bi, Jun Tan
      Pages 117-133

    3. EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition

      • Yingnan Fu, Tingting Liu, Ming Gao, Aoying Zhou
      Pages 134-151

    4. Semantic Graph Representation Learning for Handwritten Mathematical Expression Recognition

      • Zhuang Liu, Ye Yuan, Zhilong Ji, **feng Bai, **ang Bai
      Pages 152-166

    5. An Encoder-Decoder Method with Position-Aware for Printed Mathematical Expression Recognition

      • Jun Long, Quan Hong, Liu Yang
      Pages 167-181

  5. Graphics Recognition 1: (Music, Chem, Charts, Figures)

    1. Front Matter

      Pages 183-183
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    2. A Holistic Approach for Aligned Music and Lyrics Transcription

      • Juan C. Martinez-Sevilla, Antonio Rios-Vila, Francisco J. Castellanos, Jorge Calvo-Zaragoza
      Pages 185-201

    3. A Multi-level Synthesis Strategy for Online Handwritten Chemical Equation Recognition

      • Haoyang Shen, **rong Li, Jianmin Lin, Wei Wu
      Pages 202-217

    4. Context-Aware Chart Element Detection

      • Pengyu Yan, Saleem Ahmed, David Doermann
      Pages 218-233

    5. SCI-3000: A Dataset for Figure, Table and Caption Extraction from Scientific PDFs

      • Filip Darmanović, Allan Hanbury, Markus Zlabinger
      Pages 234-251

  6. Document NLP

    1. Front Matter

      Pages 253-253
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Other volumes

  1. Document Analysis and Recognition - ICDAR 2023

  2. Document Analysis and Recognition - ICDAR 2023

  3. Document Analysis and Recognition - ICDAR 2023

  4. Document Analysis and Recognition - ICDAR 2023

  5. Document Analysis and Recognition - ICDAR 2023

  6. Document Analysis and Recognition - ICDAR 2023

  7. Document Analysis and Recognition – ICDAR 2023 Workshops

  8. Document Analysis and Recognition – ICDAR 2023 Workshops

Editors and Affiliations

  • TU Dortmund University, Dortmund, Germany

    Gernot A. Fink

  • Adobe, College Park, USA

    Rajiv Jain

  • Osaka Metropolitan University, Osaka, Japan

    Koichi Kise

  • Rochester Institute of Technology, Rochester, USA

    Richard Zanibbi

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