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International Journal on Document Analysis and Recognition (IJDAR)

International Journal on Document Analysis and Recognition (IJDAR) OnlineFirst articles

21.07.2021 | Special Issue Paper

Beyond document object detection: instance-level segmentation of complex layouts

Information extraction is a fundamental task of many business intelligence services that entail massive document processing. Understanding a document page structure in terms of its layout provides contextual support which is helpful in the …

14.07.2021 | Original Paper

MRZ code extraction from visa and passport documents using convolutional neural networks

Detecting and extracting information from the machine-readable zone (MRZ) on passports and visas is becoming increasingly important for verifying document authenticity. However, computer vision methods for performing similar tasks, such as optical …

08.07.2021 | Special Issue Paper

Revealing a history: palimpsest text separation with generative networks

A palimpsest is a historical manuscript in which the original text (termed under-text) was erased and overwritten with another script in order to recycle the parchment. One of the main challenges in studying palimpsests is to reveal the …

30.06.2021 | Original Paper

Extracting text from scanned Arabic books: a large-scale benchmark dataset and a fine-tuned Faster-R-CNN model

Datasets of documents in Arabic are urgently needed to promote computer vision and natural language processing research that addresses the specifics of the language. Unfortunately, publicly available Arabic datasets are limited in size and …

24.06.2021 | Special Issue Paper

EAML: ensemble self-attention-based mutual learning network for document image classification

In the recent past, complex deep neural networks have received huge interest in various document understanding tasks such as document image classification and document retrieval. As many document types have a distinct visual style, learning only …

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Über diese Zeitschrift

Sponsored by the International Association for Pattern Recognition, this journal is focused on publishing articles that cover all areas related to document analysis and recognition. This includes contributions dealing with computer recognition of characters, symbols, text, lines, graphics, images, handwriting, signatures, as well as automatic analyses of the overall physical and logical structures of documents, with the ultimate objective of a high-level understanding of their semantic content.

The International Journal on Document Analysis and Recognition (IJDAR) publishes articles of four primary types: original research papers, correspondence, overviews and summaries, and system descriptions. It also features special issues on active areas of research.

Currently indexed in:
Academic Search Alumni Edition, Academic Search Complete, Academic Search Premier, Bibliography of Linguistic Literature, Compendex, Compuscience, Computer Science Index, Current Abstracts, Current Contents/Engineering, Computing, and Technology, DBLP, Google, INSPEC, Journal Citation Reports/Science Edition, OCLC ArticleFirst Database, OCLC FirstSearch Electronic Collections Online, PASCAL, SCOPUS, Science Citation Index Expanded, Summon by Serial Solutions, TOC Premier.

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