Document Analysis and Recognition - ICDAR 2023 Workshops (eBook, PDF)

San José, CA, USA, August 24-26, 2023, Proceedings, Part II
Redaktion: Coustaty, Mickael; Fornés, Alicia

• Format: PDF

Produktbeschreibung

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 Machine Learning (WML).

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 321
• Erscheinungstermin: 14. August 2023
• Englisch
• ISBN-13: 9783031415012
• Artikelnr.: 68598989

Inhaltsangabe

Typefaces and Ligatures in Printed Arabic Text: A Deep Learning-Based OCR Perspective.- Leveraging Knowledge Graph Embeddings to Enhance Contextual Representations for Relation Extraction.- Extracting Key-Value Pairs in Business Documents.- Long-Range Transformer Architectures for Document Understanding.-Pre-training transformers for Corporate Documents Understanding.- Transformer-Based Neural Machine Translation for Post-OCR Error Correction in Cursive Text.- Arxiv Tables: Document Understanding Challenge Linking Texts and Tables.- Subgraph-Induced Extraction Technique for Information (SETI) from Administrative Documents.- Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs.- A Clustering Approach Combining Lines and Text Detection for Table Extraction.- Absformer: Transformer-Based Model for Unsupervised Multi-Document Abstractive Summarization.- A Comparison of Demographic Attributes Detection from Handwriting Based on Traditional and Deep Learning Methods.- A New Optimization Approach to Improve an Ensemble Learning Model: Application to Persian/Arabic Handwritten Character Recognition.- BN-DRISHTI: Bangla Document Recognition Through Instance-level Segmentation of Handwritten Text Images.- Text Line Detection and Recognition of Greek Polytonic Documents.- A Comprehensive Handwritten Paragraph Text Recognition System: LexiconNet.- Local Style Awareness of Font Images.- Fourier Feature-Based CBAM and Vision Transformer for Text Detection in Drone Images.- Document Binarization with Quaternionic Double Discriminator Generative Adversarial Network.- Crosslingual Handwritten Text Generation Using GANs.- Knowledge Integration inside Multitask Network for Analysis of Unseen ID Types.