Document Analysis and Recognition – ICDAR 2023 Workshops
Springer International Publishing (Verlag)
978-3-031-41500-5 (ISBN)
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).
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.
| Erscheinungsdatum | 16.08.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XXIII, 321 p. 196 illus., 95 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 530 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Schlagworte | Computational Paleography • Deep learning • digital humanities • Document Image Analysis and Recognition • Graphics Recognition • Natural Language Processing • Optical Character Recognition • Personalized Document Analysis • Table Extraction |
| ISBN-10 | 3-031-41500-0 / 3031415000 |
| ISBN-13 | 978-3-031-41500-5 / 9783031415005 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
