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Zeitschrift

International Journal on Document Analysis and Recognition (IJDAR)

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

16.06.2018 | Original Paper

Augmented incremental recognition of online handwritten mathematical expressions

This paper presents an augmented incremental recognition method for online handwritten mathematical expressions (MEs). If an ME is recognized after all strokes are written (batch recognition), the waiting time increases significantly when the ME …

15.06.2018 | Original Paper

A comprehensive study of hybrid neural network hidden Markov model for offline handwritten Chinese text recognition

This paper proposes an effective segmentation-free approach using a hybrid neural network hidden Markov model (NN-HMM) for offline handwritten Chinese text recognition (HCTR). In the general Bayesian framework, the handwritten Chinese text line is …

09.06.2018 | Special Issue Paper

Learning to detect, localize and recognize many text objects in document images from few examples

The current trend in object detection and localization is to learn predictions with high capacity deep neural networks trained on a very large amount of annotated data and using a high amount of processing power. In this work, we particularly …

30.05.2018 | Original Paper

Fully convolutional network with dilated convolutions for handwritten text line segmentation

We present a learning-based method for handwritten text line segmentation in document images. Our approach relies on a variant of deep fully convolutional networks (FCNs) with dilated convolutions. Dilated convolutions allow to never reduce the …

23.04.2018 | Special Issue Paper

Fixed-sized representation learning from offline handwritten signatures of different sizes

Methods for learning feature representations for offline handwritten signature verification have been successfully proposed in recent literature, using deep convolutional neural networks to learn representations from signature pixels. Such methods …

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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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