Skip to main content


International Journal on Document Analysis and Recognition (IJDAR)

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

26.07.2018 | Original Paper

A combined strategy of analysis for the localization of heterogeneous form fields in ancient pre-printed records

This paper deals with the location of handwritten fields in old pre-printed registers. The images present the difficulties of old and damaged documents, and we also have to face the difficulty of extracting the text due to the great interaction …

02.07.2018 | Special Issue Paper

Integrating scattering feature maps with convolutional neural networks for Malayalam handwritten character recognition

Convolutional neural network (CNN)-based deep learning architectures are the state-of-the-art in image-based pattern recognition applications. The receptive filter fields in convolutional layers are learned from training data patterns …

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 …

Aktuelle Ausgaben

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.

Weitere Informationen

Premium Partner

Neuer Inhalt

BranchenIndex Online

Die B2B-Firmensuche für Industrie und Wirtschaft: Kostenfrei in Firmenprofilen nach Lieferanten, Herstellern, Dienstleistern und Händlern recherchieren.



Product Lifecycle Management im Konzernumfeld – Herausforderungen, Lösungsansätze und Handlungsempfehlungen

Für produzierende Unternehmen hat sich Product Lifecycle Management in den letzten Jahrzehnten in wachsendem Maße zu einem strategisch wichtigen Ansatz entwickelt. Forciert durch steigende Effektivitäts- und Effizienzanforderungen stellen viele Unternehmen ihre Product Lifecycle Management-Prozesse und -Informationssysteme auf den Prüfstand. Der vorliegende Beitrag beschreibt entlang eines etablierten Analyseframeworks Herausforderungen und Lösungsansätze im Product Lifecycle Management im Konzernumfeld.
Jetzt gratis downloaden!