Document Analysis and Recognition - ICDAR 2021 : 16th International Conference, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part I / edited by Josep Lladós, Daniel Lopresti, Seiichi Uchida.

Format:

Book

Contributor:

Lladós Masllorens, Josep, Editor.

Lopresti, Daniel., Editor.

Uchida, Seiichi., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12821

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12821

Language:

English

Subjects (All):

Image processing-Digital techniques.

Computer vision.

Computer engineering.

Computer networks.

Machine learning.

Natural language processing (Computer science).

Social sciences-Data processing.

Education-Data processing.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer Engineering and Networks.

Machine Learning.

Natural Language Processing (NLP).

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Computer Engineering and Networks.

Machine Learning.

Natural Language Processing (NLP).

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Physical Description:

1 online resource (XIX, 650 pages) : 223 illustrations, 198 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports. The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition.

Contents:

Historical Document Analysis 1

BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation

Pho(SC)Net: An Approach Towards Zero-shot Word Image Recognition in Historical Documents

Versailles-FP dataset: Wall Detection in Ancient Floor Plans

Graph Convolutional Neural Networks for Learning Attribute Representations for Word Spotting

Context Aware Generation of Cuneiform Signs

Adaptive Scaling for Archival Table Structure Recognition

Document Analysis Systems

LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment

VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relations

Layout-Parser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Understanding and Mitigating the Impact of Model Compression for Document Image Classification

Hierarchical and Multimodal Classification of Images from Soil Remediation Reports

Competition and Collaboration in Document Analysis and Recognition

Handwriting Recognition

2D Self-Attention Convolutional Recurrent Network for Offline Handwritten Text Recognition

Handwritten Text Recognition with Convolutional Prototype Network and Most Aligned Frame Based CTC Training

Online Spatio-Temporal 3D Convolutional Neural Network for Early Recognition of Handwritten Gestures

Mix-Up Augmentation for Oracle Character Recognition with Imbalanced Data Distribution

Radical Composition Network for Chinese Character Generation

SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators

Scene Text Detection and Recognition

Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition

Text Detection by Jointly Learning Character and Word Regions

Vision Transformer for Fast and Efficient Scene Text Recognition

Look, Read and Ask: Learning to Ask Questions by Reading Text in Images

CATNet: Scene Text Recognition Guided by Concatenating Augmented Text Features

Explore Hierarchical Relations Reasoning and Global Information Aggregation

Historical Document Analysis 2

One-Model Ensemble-Learning for Text Recognition of Historical Printings

On the use of attention in deep learning based denoising method for ancient Cham inscription images

Visual FUDGE: Form Understanding via Dynamic Graph Editing

Annotation-Free Character Detection in Historical Vietnamese Stele Images

Document Image Processing

DocReader: Bounding-Box Free Training of a Document Information Extraction Model

Document Dewarping with Control Points

Unknown-box Approximation to Improve Optical Character Recognition Performance

Document Domain Randomization for Deep Learning Document Layout Extraction

NLP for Document Understanding

Distilling the Documents for Relation Extraction by Topic Segmentation

LAMBERT: Layout-Aware Language Modeling for Information Extraction

ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents

Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts

Graphics, Diagram, and Math Recognition

Towards an efficient framework for Data Extraction from Chart Images

Geometric Object 3D Reconstruction From Single Line Drawings Image Based on a Network for Classification and Sketch Extraction

DiagramNet: Hand-drawn Diagram Recognition using Visual Arrow-relation Detection

Formula Citation Graph Based Mathematical Information Retrieval.

Other Format:

Printed edition:

ISBN:

978-3-030-86549-8

9783030865498

Access Restriction:

Restricted for use by site license.