Document Analysis and Recognition - ICDAR 2021 16th International Conference, Lausanne, Switzerland, September 5-10, 2021, Proceedings, Part II / [electronic resource] :
edited by Josep Lladós, Daniel Lopresti, Seiichi Uchida.
- 1st ed. 2021.
- XX, 873 p. 329 illus., 277 illus. in color. online resource.
- Image Processing, Computer Vision, Pattern Recognition, and Graphics, 12822 3004-9954 ; .
- Image Processing, Computer Vision, Pattern Recognition, and Graphics, 12822 .
Document Analysis for Literature Search -- Towards Document Panoptic Segmentation with Pinpoint Accuracy: Method and Evaluation -- A Math Formula Extraction and Evaluation Framework for PDF Documents -- Toward Automatic Interpretation of 3D Plots -- Document Summarization and Translation -- Can Text Summarization Enhance the Headline Stance Detection Task? Benefits and Drawbacks -- The Biased Coin Flip Process for Nonparametric Topic Modeling.-CoMSum and SIBERT: A Dataset and Neural Model for Query-Based Multi-Document Summarization -- RTNet: An End-to-End Method for Handwritten Text Image Translation -- NTable: A Dataset for Camera-based Table Detection -- Multimedia document analysis -- Label Selection Algorithm Based on Boolean Interpolative Decomposition with Sequential Backward Selection for Multi-label Classification -- GSSF: A Generative Sequence Similarity Function based on a Seq2Seq model for clustering online handwritten mathematical answers -- C2VNet: A Deep Learning Framework Towards Comic Strip to Audio-Visual Scene Synthesis -- LSTMVAEF: Vivid Layout via LSTM-based Variational Autoencoder Framework -- Mobile Text Recognition -- HCRNN: A Novel Architecture for Fast Online Handwritten Stroke Classification -- RFDoc: memory efficient local descriptors for ID documents localization and classification -- Dynamic Receptive Field Adaptation for Attention-Based Text Recognition -- Context-Free TextSpotter for Real-Time and Mobile End-to-End Text Detection and Recognition -- MIDV-LAIT: a challenging dataset for recognition of IDs with Perso-Arabic, Thai, and Indian scripts,. Determining optimal frame processing strategies for real-time document recognition systems -- Document Analysis for Social Good -- Embedded Attributes for Cuneiform Sign Spotting -- Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach -- Two-Step Fine-Tuned Convolutional Neural Networks for Multi-Label Classification of Children's Drawings -- DCINN: Deformable Convolution and Inception Based Neural Network for Tattoo Text Detection through Skin Region -- Sparse Document Analysis using Beta-Liouville Naive Bayes with Vocabulary Knowledge -- Automatic Signature-based Writer Identification in Mixed-script Scenarios -- Indexing and Retrieval of Documents -- Indexing and Retrieval of Documents -- Learning to Rank Words: Optimizing Ranking Metrics for Word Spotting -- A-VLAD: An End-to-End Attention-based Neural Network for Writer Identification in Historical Documents -- Manga-MMTL: multimodal multitask transfer learning for manga character analysis -- Probabilistic Indexing and Search for Hyphenated Words -- Physical and Logical Layout Analysis -- SandSlide: Automatic Slideshow Normalization -- Digital Editions as Distant Supervision for Layout Analysis of Printed Books -- Palmira: A Deep Deformable Network for Instance Segmentation of Dense and Uneven Layouts in Handwritten Manuscripts -- Page Layout Analysis System for Unconstrained Historic Documents -- Improved Graph Methods for Table Layout Understanding -- Unsupervised learning of text line segmentation by differentiating coarse patterns -- Recognition of Tables and Formulas -- Rethinking Table Structure Recognition Using Sequence Labeling Methods -- TabLeX: A Benchmark Dataset for Structure and Content Information Extraction from Scientific Tables -- Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer -- TabAug: Data Driven Augmentation for Enhanced Table Structure Recognition -- An Encoder-Decoder Approach to Handwritten Mathematical Expression Recognition with Multi-Head Attention and Stacked Decoder -- Global Context for improving recognition of Online Handwritten Mathematical Expressions -- Image-based Relation Classification Approach for Table Structure Recognition -- Image to LaTeX with Graph Neural Network for Mathematical Formula Recognition -- NLP for Document Understanding -- A Novel Method for AutomatedSuggestion of Similar Software Incidents using 2-Stage Filtering: Findings on Primary Data -- Research on pseudo-label technology for multi-label news classification -- Information Extraction from Invoices -- Are You Really Complaining? A Multi-task Framework for Complaint Identification, Emotion and Sentiment Classification -- Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer -- Data Centric Domain Adaptation for Historical Text with OCR Errors -- Temporal Ordering of Events via Deep Neural Networks -- Document Collection Visual Question Answering -- Dialogue Act Recognition using Visual Information -- Are End-to-End Systems Really Necessary for NER on Handwritten Document Images? -- Training Bi-Encoders for Word Sense Disambiguation -- DeepCPCFG: Deep Learning and Context Free Grammars for End-to-End Information Extraction -- Consideration of the word's neighborhood in GATs for information extraction in semi-structured documents.
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: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding.
9783030863319
10.1007/978-3-030-86331-9 doi
Image processing--Digital techniques. Computer vision. Computer engineering. Computer networks . Machine learning. Natural language processing (Computer science). Education--Data processing. Social sciences--Data processing. Computer Imaging, Vision, Pattern Recognition and Graphics. Computer Engineering and Networks. Machine Learning. Natural Language Processing (NLP). Computers and Education. Computer Application in Social and Behavioral Sciences.