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Document Analysis and Recognition – ICDAR 2023 Workshops

San José, CA, USA, August 24–26, 2023, Proceedings, Part II

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Mickael Coustaty

    1. University of La Rochelle, La Rochelle, France

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    You can also search for this editor in PubMed   Google Scholar

  2. Alicia Fornés

    1. Autonomous University of Barcelona, Bellaterra, Spain

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14194)

Included in the following conference series:

Conference proceedings info: ICDAR 2023.

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Table of contents (21 papers)

  1. Front Matter

    Pages i-xxiii
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  2. VINALDO

    1. Front Matter

      Pages 1-3
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    2. Typefaces and Ligatures in Printed Arabic Text: A Deep Learning-Based OCR Perspective

      • Omar Alhubaiti, Irfan Ahmad
      Pages 5-18

    3. Leveraging Knowledge Graph Embeddings to Enhance Contextual Representations for Relation Extraction

      • Fréjus A. A. Laleye, Loïc Rakotoson, Sylvain Massip
      Pages 19-31

    4. Extracting Key-Value Pairs in Business Documents

      • Eliott Thomas, Dipendra Sharma Kafle, Ibrahim Souleiman Mahamoud, Aurélie Joseph, Mickael Coustaty, Vincent Poulain d’Andecy
      Pages 32-46

    5. Long-Range Transformer Architectures for Document Understanding

      • Thibault Douzon, Stefan Duffner, Christophe Garcia, Jérémy Espinas
      Pages 47-64

    6. KAP: Pre-training Transformers for Corporate Documents Understanding

      • Ibrahim Souleiman Mahamoud, Mickaël Coustaty, Aurélie Joseph, Vincent Poulain d’Andecy, Jean-Marc Ogier
      Pages 65-79

    7. Transformer-Based Neural Machine Translation for Post-OCR Error Correction in Cursive Text

      • Nehal Yasin, Imran Siddiqi, Momina Moetesum, Sadaf Abdul Rauf
      Pages 80-93

    8. Arxiv Tables: Document Understanding Challenge Linking Texts and Tables

      • Karolina Konopka, Michał Turski, Filip Graliński
      Pages 94-107

    9. Subgraph-Induced Extraction Technique for Information (SETI) from Administrative Documents

      • Dipendra Sharma Kafle, Eliott Thomas, Mickael Coustaty, Aurélie Joseph, Antoine Doucet, Vincent Poulain d’Andecy
      Pages 108-122

    10. Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs

      • Alejandro Peña, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Marcos Grande, Íñigo Puente et al.
      Pages 123-138

    11. A Clustering Approach Combining Lines and Text Detection for Table Extraction

      • Karima Boutalbi, Visar Sylejmani, Pierre Dardouillet, Olivier Le Van, Kave Salamatian, Hervé Verjus et al.
      Pages 139-145

  3. WML

    1. Front Matter

      Pages 147-150
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    2. Absformer: Transformer-Based Model for Unsupervised Multi-Document Abstractive Summarization

      • Mohamed Trabelsi, Huseyin Uzunalioglu
      Pages 151-166

    3. A Comparison of Demographic Attributes Detection from Handwriting Based on Traditional and Deep Learning Methods

      • Fahimeh Alaei, Alireza Alaei
      Pages 167-179

    4. A New Optimization Approach to Improve an Ensemble Learning Model: Application to Persian/Arabic Handwritten Character Recognition

      • Omid Motamedisedeh, Faranak Zagia, Alireza Alaei
      Pages 180-194

    5. BN-DRISHTI: Bangla Document Recognition Through Instance-Level Segmentation of Handwritten Text Images

      • Sheikh Mohammad Jubaer, Nazifa Tabassum, Md Ataur Rahman, Mohammad Khairul Islam
      Pages 195-212

    6. Text Line Detection and Recognition of Greek Polytonic Documents

      • Panagiotis Kaddas, Basilis Gatos, Konstantinos Palaiologos, Katerina Christopoulou, Konstantinos Kritsis
      Pages 213-225

    7. A Comprehensive Handwritten Paragraph Text Recognition System: LexiconNet

      • Lalita Kumari, Sukhdeep Singh, Vaibhav Varish Singh Rathore, Anuj Sharma
      Pages 226-241

    8. Local Style Awareness of Font Images

      • Daichi Haraguchi, Seiichi Uchida
      Pages 242-256
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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

Keywords

About this book

This two-volume set LNCS 14193-14194 constitutes the proceedings of International Workshops co-located with the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, held in San José, CA, USA, during August 21–26, 2023.

The total of 43 regular papers presented in this book were carefully selected from 60 submissions. 

Part I contains 22 regular papers that stem from the following workshops:

ICDAR 2023 Workshop on Computational Paleography (IWCP);

ICDAR 2023 Workshop on Camera-Based Document Analysis and Recognition (CBDAR);

ICDAR 2023 International Workshop on Graphics Recognition (GREC);

ICDAR 2023 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA);

Part II contains 21 regular papers that stem from the following workshops:

ICDAR 2023 Workshop on Machine Vision and NLP for Document Analysis (VINALDO);

ICDAR 2023 International Workshop on MachineLearning (WML).

 

Editors and Affiliations

  • University of La Rochelle, La Rochelle, France

    Mickael Coustaty

  • Autonomous University of Barcelona, Bellaterra, Spain

    Alicia Fornés

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