| TÃtulo : |
16th International Conference, Lausanne, Switzerland, September 5–10, 2021, Proceedings, Part I |
| Tipo de documento: |
documento electrónico |
| Autores: |
Lladós, Josep, ; Lopresti, Daniel, ; Uchida, Seiichi, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XIX, 650 p. 223 ilustraciones, 198 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-86549-8 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Procesamiento de imágenes Visión por computador IngenierÃa Informática Red de computadoras Aprendizaje automático Procesamiento del lenguaje natural (Informática) Ciencias sociales Imágenes por computadora visión reconocimiento de patrones y gráficos IngenierÃa Informática y Redes Procesamiento del lenguaje natural (PNL) Aplicación informática en ciencias sociales y del comportamiento Computadoras y Educación |
| Ãndice Dewey: |
6 |
| Resumen: |
Este conjunto de cuatro volúmenes de LNCS 12821, LNCS 12822, LNCS 12823 y LNCS 12824 constituye las actas arbitradas de la 16.ª Conferencia Internacional sobre Análisis y Reconocimiento de Documentos, ICDAR 2021, celebrada en Lausana, Suiza, en septiembre de 2021. Los 182 artÃculos completos fueron Se revisan y seleccionan cuidadosamente entre 340 presentaciones y se presentan con 13 informes de competencia. Los artÃculos están organizados en las siguientes secciones temáticas: análisis de documentos históricos, sistemas de análisis de documentos, reconocimiento de escritura a mano, detección y reconocimiento de textos de escenas, procesamiento de imágenes de documentos, procesamiento del lenguaje natural (NLP) para la comprensión de documentos y reconocimiento de gráficos, diagramas y matemáticas. |
| Nota de contenido: |
Historical Document Analysis 1 -- BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation -- Pho(SC)Net: An Approach Towards Zero-shot Word Image Recognition in Historical Documents -- Versailles-FP dataset: Wall Detection in Ancient Floor Plans -- Graph Convolutional Neural Networks for Learning Attribute Representations for Word Spotting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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
16th International Conference, Lausanne, Switzerland, September 5–10, 2021, Proceedings, Part I [documento electrónico] / Lladós, Josep, ; Lopresti, Daniel, ; Uchida, Seiichi, . - 1 ed. . - [s.l.] : Springer, 2021 . - XIX, 650 p. 223 ilustraciones, 198 ilustraciones en color. ISBN : 978-3-030-86549-8 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Procesamiento de imágenes Visión por computador IngenierÃa Informática Red de computadoras Aprendizaje automático Procesamiento del lenguaje natural (Informática) Ciencias sociales Imágenes por computadora visión reconocimiento de patrones y gráficos IngenierÃa Informática y Redes Procesamiento del lenguaje natural (PNL) Aplicación informática en ciencias sociales y del comportamiento Computadoras y Educación |
| Ãndice Dewey: |
6 |
| Resumen: |
Este conjunto de cuatro volúmenes de LNCS 12821, LNCS 12822, LNCS 12823 y LNCS 12824 constituye las actas arbitradas de la 16.ª Conferencia Internacional sobre Análisis y Reconocimiento de Documentos, ICDAR 2021, celebrada en Lausana, Suiza, en septiembre de 2021. Los 182 artÃculos completos fueron Se revisan y seleccionan cuidadosamente entre 340 presentaciones y se presentan con 13 informes de competencia. Los artÃculos están organizados en las siguientes secciones temáticas: análisis de documentos históricos, sistemas de análisis de documentos, reconocimiento de escritura a mano, detección y reconocimiento de textos de escenas, procesamiento de imágenes de documentos, procesamiento del lenguaje natural (NLP) para la comprensión de documentos y reconocimiento de gráficos, diagramas y matemáticas. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
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16th International Conference, Lausanne, Switzerland, September 5–10, 2021, Proceedings, Part I
