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Title:
Document Analysis and Recognition - ICDAR 2023 Workshops San José, CA, USA, August 24-26, 2023, Proceedings, Part II
Author:
Coustaty, Mickael. editor.
ISBN:
9783031415012
Edition:
1st ed. 2023.
Physical Description:
XXIII, 321 p. 196 illus., 95 illus. in color. online resource.
Series:
Lecture Notes in Computer Science, 14194
Contents:
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.
Added Corporate Author:
Electronic Access:
https://doi.org/10.1007/978-3-031-41501-2Copies:
Available:*
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