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Produktbild: Document Analysis and Recognition – ICDAR 2021
Band 12821

Document Analysis and Recognition – ICDAR 2021 16th International Conference, Lausanne, Switzerland, September 5–10, 2021, Proceedings, Part I

Aus der Reihe Lecture Notes in Computer Science

98,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.09.2021

Abbildungen

XIX, 650 p. 223 illus., 198 illus. in color.

Herausgeber

Josep Lladós + weitere

Verlag

Springer

Seitenzahl

650

Maße (L/B/H)

23,5/15,5/3,6 cm

Gewicht

1001 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-86548-1

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.09.2021

Abbildungen

XIX, 650 p. 223 illus., 198 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

650

Maße (L/B/H)

23,5/15,5/3,6 cm

Gewicht

1001 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-86548-1

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Document Analysis and Recognition – ICDAR 2021

  • Historical Document Analysis 1.-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Maps for Semi-automatic Layout Annotation.- Pho(SC)Net: An Approach Towards Zero-shot Word Image Recognition in Historical Documents.- Versailles-FP dataset: Wall Detection in Ancient Floor Plans.- Graph Convolutional Neural Networks for Learning Attribute Representations for Word Spotting.-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.