Document Analysis and Recognition - ICDAR 2021 : 16th International Conference, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part IV / 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, 12824

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12824

Language:

English

Subjects (All):

Image processing-Digital techniques.

Computer vision.

Machine learning.

Computer engineering.

Computer networks.

Natural language processing (Computer science).

Social sciences-Data processing.

Education-Data processing.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Machine Learning.

Computer Engineering and Networks.

Natural Language Processing (NLP).

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Machine Learning.

Computer Engineering and Networks.

Natural Language Processing (NLP).

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Physical Description:

1 online resource (XX, 799 pages) : 312 illustrations, 240 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sections: scene text detection and recognition, document classification, gold-standard benchmarks and data sets, historical document analysis, and handwriting recognition. In addition, the volume contains results of 13 scientific competitions held during ICDAR 2021.

Contents:

Scene Text Detection and Recognition

HRRegionNet: Chinese Character Segmentation in Historical Documents with Regional Awareness

Fast Text volume Non-text Classification of Images

Mask Scene Text Recognizer

Rotated Box Is Back: An Accurate Box Proposal Network for Scene Text Detection

Heterogeneous Network Based Semi-supervised Learning For Scene Text Recognition

Scene Text Detection with Scribble Line

EEM: An End-to-end Evaluation Metric for Scene Text Detection and Recognition

SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models

Fast Recognition for Multidirectional and Multi-Type License Plates with 2D Spatial Attention

A Multi-level Progressive Rectification Mechanism for Irregular Scene Text Recognition

Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognition

FEDS - Filtered Edit Distance Surrogate

Bidirectional Regression for Arbitrary-Shaped Text Detection

Document Classification

VML-HP: Hebrew paleography dataset

Open Set Authorship Attribution toward Demystifying Victorian Periodicals

A More Effective Sentence-Wise Text Segmentation Approach using BERT

Data Augmentation for Writer Identification Using a Cognitive Inspired Model

Key-guided Identity Document Classification Method by Graph Attention Network

Document Image Quality Assessment via Explicit Blur and Text Size Estimation

Analyzing the potential of Zero-Shot Recognition for Document Image Classification

Gender Detection Based on Spatial Pyramid Matching

EDNets: Deep Feature Learning for Document Image Classification based on Multi-view Encoder-Decoder Neural Networks

Fast End-to-end Deep Learning Identity Document Detection, Classification and Cropping

Gold-Standard Benchmarks and Data Sets

Image Collation: Matching illustrations in manuscripts

Revisiting the Coco Panoptic Metric to Enable Visual and Qualitative Analysis of Historical Map Instance Segmentation

A Large Multi-Target Dataset of Common Bengali Handwritten Graphemes

GNHK: A Dataset for English Handwriting in the Wild

Personalizing Handwriting Recognition Systems with Limited User-Specific Samples

An Efficient Local Word Augment Approach for Mongolian Handwritten Script Recognition

IIIT-INDIC-HW-WORDS: A Dataset for Indic Handwritten Text Recognition

Historical Document Analysis

AT-ST: Self-Training Adaptation Strategy for OCR in Domains with Limited Transcriptions

TS-Net: OCR Trained to Switch Between Text Transcription Styles

Handwriting Recognition with Novelty

Vectorization of Historical Maps Using Deep Edge Filtering and Closed Shape Extraction

Data Augmentation Based on CycleGAN for Improving Woodblock-printing Mongolian Words Recognition

SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization

Handwriting Recognition

Recognizing Handwritten Chinese Texts with Insertion and Swapping Using A Structural Attention Network

Strikethrough Removal From Handwritten Words Using CycleGANs

Iterative Weighted Transductive Learning for Handwriting Recognition

Competition Reports

ICDAR 2021 Competition on Scientific Literature Parsing

ICDAR 2021 Competition on Historical Document Classification

ICDAR 2021 Competition on Document Visual Question Answering

ICDAR 2021 Competition on Scene Video Text Spotting

ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment

ICDAR 2021 Competition on Components Segmentation Task of Document Photos

ICDAR 2021 Competition on Historical Map Segmentation

ICDAR 2021 Competition on Time-Quality Document Image Binarization

ICDAR 2021 Competition on On-Line Signature Verification

ICDAR 2021 Competition on Script Identification in the Wild

ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX

ICDAR 2021 Competition on Multimodal Emotion Recognition on Comics Scenes

ICDAR 2021 Competition on Mathematical Formula Detection.

Other Format:

Printed edition:

ISBN:

978-3-030-86337-1

9783030863371

Access Restriction:

Restricted for use by site license.