IJDAR Discount for IAPR Members (repost) ---------------------------------------- IAPR is pleased to announce a partnership agreement with Springer, the publisher of IJDAR, the International Journal on Document Analysis and Recognition. This new agreement will allow IAPR members to receive a subscription to the electronic version of IJDAR at a discount of nearly 50%. For additional details, see the links below: - - [http://www.iapr.org/publications/intjrnlsub.php](http://www.iapr.org/publications/intjournal.php) **Koichi Kise, Daniel Lopresti and Simone Marinai, IJDAR Editors-in-Chief** ( , , ) Datasets (repost) ================= TC-11 maintains a colletion of datasets that can be found online in the [TC-11 Datasets Repository](http://www.iapr-tc11.org/mediawiki/index.php/Datasets). If you have new datasets (e.g., from competitions) that you wish to share with the research community, please contact the TC-11 Dataset Curator (contact information is below). **Andreas Fischer (TC-11 Dataset Curator)** () Careers ======= IRISA/INSA Rennes (France): Research Engineer/PostDoc Position (3 Years - repost) --------------------------------------------------------------------------------- **Analysis systems for serial sources in collections of historical image documents** **Pdf version:** **Important Dates** September 1, 2018 - August 31, 2021 Contract period **IRISA - Intuidoc** IRISA is a joint research center for Informatics, including Robotics and Image and Signal Processing. 800 people, 40 teams, explore the world of digital sciences to find applications in healthcare, ecology-environment, cyber-security, transportation, multimedia, and industry. INSA Rennes is one of the 8 trustees of IRISA. The Intuidoc team () conducts research on the topic of document image recognition. Since many years, the team proposes a system, called DMOS-PI method, for document structure analysis of documents. This DMOS-PI method is used for document recognition, or field extraction in archive documents, handwritten contents damaged documents (musical scores, archives, newspapers, letters, electronic schema, etc.). **EURHISFIRM project** EURHISFIRM European project aims at developing a research infrastructure to connect, collect, collate, align, and share reliable long-run company-level data for Europe to enable researchers, policymakers and other stakeholders to analyze, develop, and evaluate effective strategies to promote investment and economic growth. To achieve this goal, EURHISFIRM develops innovative tools to spark a "Big data" revolution in the historical social sciences and to open access to cultural heritage. EURHISFIRM is a project funded by the European Commission within the Infrastructure Development Program of Horizon 2020. The first phase of the Infrastructure Development Program lasts for three years. It aims at developing an in-depth design study of the Research Infrastructure. After this phase, Development and Consolidation Phases follow if further applications will be successful. EURHISFIRM brings together eleven research institutions in economics, history, information technologies and data science from seven European countries. **Position to be filled** - Position: Post-doctoral fellow / Research Engineer - Time commitment: Full-time - Duration of the contract: up to 36 months, starting as soon a possible - Supervisors: Bertrand Coüasnon and Aurélie Lemaitre - Indicative salary: Up to €36 000 gross annual salary (according to experience), with social security benefits - Location: IRISA -- Rennes, France **Missions** The post-doctoral fellow / research engineer will be working on two tasks of EURHISFIRM workflow: the architecture of an adaptable system for document recognition, and the implementation of a generic structure layout extraction module. The scientific challenge will be to extract information from various printed serial sources. Due to the large variety of those documents, a flexible and easy-to-adapt document recognition system is designed. For that purpose, the system will be based on a modeling of knowledge not only at the page level but also at the collection level in interaction with experts of the historical sources. Thus, redundancies between pages will be used to make the system more reliable and reduce manual corrections while obtaining a high recognition quality. The system will we based on the DMOS-PI method which gives a framework for the analysis of collections of documents. It enables to share information from the collection between the pages, thanks to an iterative mechanism of analysis. This mechanism also makes it possible to integrate an asynchronous interaction between automatic analysis and human operators in order to limit the time of interaction by avoiding mutual waiting. This modeling of the global analysis must be able to adapt to very different kinds of documents: from very structured documents, like stock exchange lists with redundancy and strong consistency between sequences of data, up to less structured documents, like yearbooks even if, also for them, the sequence from one year to another is important for improving the recognition quality. The implementation of a generic structure extraction module will be based on the DMOS-PI method. It uses a grammatical language, EPF (Enhanced Position Formalism), to describe a general page layout, with perceptive vision mechanisms, and an iterative analysis. The system will also combine structural method with Deep Learning. For new collections, an adapted description of the document layout will be developed. This has to be done on a large range of structure levels: from very structured pages like table structures from stock exchange lists, up to a paragraph-oriented structures from yearbooks. **Applicant Requirements** - PhD, Master degree or Engineering degree in computer science - Experience in document recognition, statistical analysis or deep learning. - Fluent English - Skills in grammars and languages and/or logical programming are nice-to-have. For further information, please contact Bertrand Coüasnon () and Aurélie Lemaitre (). Applicants should send a curriculum-vitae with a list of publications and the names and email addresses of up to three references. **Bertrand Coüasnon, Director, Media and Interactions Department (IRISA)** ( ) Student Industrial Internship Opportunities (IAPR - repost) ----------------------------------------------------------- [IAPR's Industrial Liaison Committee](http://www.iapr.org/committees/committees.php?id=5&subid=53) is pleased to announce the opening of its Company Internship Brokerage List. The web page lists internship opportunities for students at different levels of education and specialism. We expect many additional internship opportunities to be listed here as the community becomes more aware of the site. IAPR Company Internship Brokerage List: **Bob Fisher, Chair, IAPR Industrial Liason Committee** ( ) Contributions and Subscriptions ================================== **Call for Contributions:** To contribute news items, please send a short email to the editor, [Richard Zanibbi](mailto:rxzvcs@cs.rit.edu). Contributions might include conference and workshop announcements or reports, career opportunities, book reviews, or anything else of interest to the TC-11 community. **Subscription:** This newsletter is sent to subscribers of the IAPR TC11 mailing list. To join the TC-11 mailing list, please click on [this link](https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=iapr-tc11&A=1). To manage your subscription, please visit the [mailing list homepage](https://www.jiscmail.ac.uk/cgi-bin/webadmin?A0=IAPR-TC11). ------------------------------------------------------------------------ IAPR TC-11 HOMEPAGE: [http://www.iapr-tc11.org](http://www.iapr-tc11.org) The IAPR is the International Association for Pattern Recognition. IAPR's Technical Committee No. 11 (TC-11) includes researchers and practitioners working with Optical Character Recognition (OCR), and more generally the analysis and recognition of information in documents.