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Author Pau Riba; Lutz Goldmann; Oriol Ramos Terrades; Diede Rusticus; Alicia Fornes; Josep Llados edit  doi
openurl 
  Title Table detection in business document images by message passing networks Type Journal Article
  Year 2022 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 127 Issue Pages 108641  
  Keywords  
  Abstract Tabular structures in business documents offer a complementary dimension to the raw textual data. For instance, there is information about the relationships among pieces of information. Nowadays, digital mailroom applications have become a key service for workflow automation. Therefore, the detection and interpretation of tables is crucial. With the recent advances in information extraction, table detection and recognition has gained interest in document image analysis, in particular, with the absence of rule lines and unknown information about rows and columns. However, business documents usually contain sensitive contents limiting the amount of public benchmarking datasets. In this paper, we propose a graph-based approach for detecting tables in document images which do not require the raw content of the document. Hence, the sensitive content can be previously removed and, instead of using the raw image or textual content, we propose a purely structural approach to keep sensitive data anonymous. Our framework uses graph neural networks (GNNs) to describe the local repetitive structures that constitute a table. In particular, our main application domain are business documents. We have carefully validated our approach in two invoice datasets and a modern document benchmark. Our experiments demonstrate that tables can be detected by purely structural approaches.  
  Address July 2022  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.162; 600.121 Approved no  
  Call Number (up) Admin @ si @ Serial 3729  
Permanent link to this record
 

 
Author Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) edit  doi
isbn  openurl
  Title 16th International Conference, 2021, Proceedings, Part III Type Book Whole
  Year 2021 Publication Document Analysis and Recognition – ICDAR 2021 Abbreviated Journal  
  Volume 12823 Issue Pages  
  Keywords  
  Abstract 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.
 
  Address Lausanne, Switzerland, September 5-10, 2021  
  Corporate Author Thesis  
  Publisher Springer Cham Place of Publication Editor Josep Llados; Daniel Lopresti; Seiichi Uchida  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-86333-3 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ Serial 3727  
Permanent link to this record
 

 
Author Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) edit  doi
isbn  openurl
  Title 16th International Conference, 2021, Proceedings, Part IV Type Book Whole
  Year 2021 Publication Document Analysis and Recognition – ICDAR 2021 Abbreviated Journal  
  Volume 12824 Issue Pages  
  Keywords  
  Abstract 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.
 
  Address Lausanne, Switzerland, September 5-10, 2021  
  Corporate Author Thesis  
  Publisher Springer Cham Place of Publication Editor Josep Llados; Daniel Lopresti; Seiichi Uchida  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-86336-4 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ Serial 3728  
Permanent link to this record
 

 
Author Mohamed Ali Souibgui; Asma Bensalah; Jialuo Chen; Alicia Fornes; Michelle Waldispühl edit  doi
openurl 
  Title A User Perspective on HTR methods for the Automatic Transcription of Rare Scripts: The Case of Codex Runicus Just Accepted Type Journal Article
  Year 2022 Publication ACM Journal on Computing and Cultural Heritage Abbreviated Journal JOCCH  
  Volume Issue Pages  
  Keywords  
  Abstract Recent breakthroughs in Artificial Intelligence, Deep Learning and Document Image Analysis and Recognition have significantly eased the creation of digital libraries and the transcription of historical documents. However, for documents in rare scripts with few labelled training data available, current Handwritten Text Recognition (HTR) systems are too constraint. Moreover, research on HTR often focuses on technical aspects only, and rarely puts emphasis on implementing software tools for scholars in Humanities. In this article, we describe, compare and analyse different transcription methods for rare scripts. We evaluate their performance in a real use case of a medieval manuscript written in the runic script (Codex Runicus) and discuss advantages and disadvantages of each method from the user perspective. From this exhaustive analysis and comparison with a fully manual transcription, we raise conclusions and provide recommendations to scholars interested in using automatic transcription tools.  
  Address July 2022  
  Corporate Author Thesis  
  Publisher ACM Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no  
  Call Number (up) Admin @ si @ Serial 3732  
Permanent link to this record
 

 
Author Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) edit  doi
isbn  openurl
  Title 16th International Conference, 2021, Proceedings, Part I Type Book Whole
  Year 2021 Publication Document Analysis and Recognition – ICDAR 2021 Abbreviated Journal  
  Volume 12821 Issue Pages  
  Keywords  
  Abstract 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.
 
  Address Lausanne, Switzerland, September 5-10, 2021  
  Corporate Author Thesis  
  Publisher Springer Cham Place of Publication Editor Josep Llados; Daniel Lopresti; Seiichi Uchida  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-86548-1 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ Serial 3725  
Permanent link to this record
 

 
Author Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) edit  doi
isbn  openurl
  Title 16th International Conference, 2021, Proceedings, Part II Type Book Whole
  Year 2021 Publication Document Analysis and Recognition – ICDAR 2021 Abbreviated Journal  
  Volume 12822 Issue Pages  
  Keywords  
  Abstract 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.
 
  Address Lausanne, Switzerland, September 5-10, 2021  
  Corporate Author Thesis  
  Publisher Springer Cham Place of Publication Editor Josep Llados; Daniel Lopresti; Seiichi Uchida  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-86330-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ Serial 3726  
Permanent link to this record
 

 
Author Josep Llados edit  openurl
  Title The 5G of Document Intelligence Type Conference Article
  Year 2021 Publication 3rd Workshop on Future of Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Lausanne; Suissa; September 2021  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ Serial 3677  
Permanent link to this record
 

 
Author Mohamed Ali Souibgui; Sanket Biswas; Sana Khamekhem Jemni; Yousri Kessentini; Alicia Fornes; Josep Llados; Umapada Pal edit  doi
openurl 
  Title DocEnTr: An End-to-End Document Image Enhancement Transformer Type Conference Article
  Year 2022 Publication 26th International Conference on Pattern Recognition (ICPR) Abbreviated Journal  
  Volume Issue Pages 1699-1705  
  Keywords  
  Abstract Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for proper usage. To address this challenge, we present a new encoder-decoder architecture based on vision transformers to enhance both machine-printed and handwritten document images, in an end-to-end fashion. The encoder operates directly on the pixel patches with their positional information without the use of any convolutional layers, while the decoder reconstructs a clean image from the encoded patches. Conducted experiments show a superiority of the proposed model compared to the state-of the-art methods on several DIBCO benchmarks. Code and models will be publicly available at: https://github.com/dali92002/DocEnTR  
  Address August 21-25, 2022 , Montréal Québec  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICPR  
  Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no  
  Call Number (up) Admin @ si @ Serial 3730  
Permanent link to this record
 

 
Author Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados edit  doi
openurl 
  Title A Generic Image Retrieval Method for Date Estimation of Historical Document Collections Type Conference Article
  Year 2022 Publication Document Analysis Systems.15th IAPR International Workshop, (DAS2022) Abbreviated Journal  
  Volume 13237 Issue Pages 583–597  
  Keywords Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG  
  Abstract Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.  
  Address La Rochelle, France; May 22–25, 2022  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number (up) Admin @ si @ Serial 3694  
Permanent link to this record
 

 
Author Josep Brugues Pujolras; Lluis Gomez; Dimosthenis Karatzas edit  doi
openurl 
  Title A Multilingual Approach to Scene Text Visual Question Answering Type Conference Article
  Year 2022 Publication Document Analysis Systems.15th IAPR International Workshop, (DAS2022) Abbreviated Journal  
  Volume Issue Pages 65-79  
  Keywords Scene text; Visual question answering; Multilingual word embeddings; Vision and language; Deep learning  
  Abstract Scene Text Visual Question Answering (ST-VQA) has recently emerged as a hot research topic in Computer Vision. Current ST-VQA models have a big potential for many types of applications but lack the ability to perform well on more than one language at a time due to the lack of multilingual data, as well as the use of monolingual word embeddings for training. In this work, we explore the possibility to obtain bilingual and multilingual VQA models. In that regard, we use an already established VQA model that uses monolingual word embeddings as part of its pipeline and substitute them by FastText and BPEmb multilingual word embeddings that have been aligned to English. Our experiments demonstrate that it is possible to obtain bilingual and multilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines.  
  Address La Rochelle, France; May 22–25, 2022  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DAS  
  Notes DAG; 611.004; 600.155; 601.002 Approved no  
  Call Number (up) Admin @ si @ Serial 3695  
Permanent link to this record
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