UID:
almahu_9949552700902882
Umfang:
XXIII, 321 p. 196 illus., 95 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2023.
ISBN:
9783031415012
Serie:
Lecture Notes in Computer Science, 14194
Inhalt:
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). .
Anmerkung:
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.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031415005
Weitere Ausg.:
Printed edition: ISBN 9783031415029
Sprache:
Englisch
DOI:
10.1007/978-3-031-41501-2
URL:
https://doi.org/10.1007/978-3-031-41501-2
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