Offline handwriting recognition systems require cropped text line images for both training
and recognition. On the one hand, the annotation of position and transcript at line level is …

In this paper, we propose a new neural network architecture for state-of-the-art handwriting
recognition, alternative to multi-dimensional long short-term memory (MD-LSTM) recurrent …

The automatic transcription of text in handwritten documents has many applications, from
automatic document processing, to indexing and document understanding. One of the most …

Methods and systems are provided for end-to-end text recognition in digitized documents of
handwritten charac ters over multiple lines without explicit line segmentation. An image is …

Text line detection and localization is a crucial step for full page document analysis, but still
suffers from heterogeneity of real life documents. In this paper, we present a new approach …

Methods and systems are provided for end-to-end text recognition in digitized documents of
handwritten charac ters over multiple lines without explicit line segmentation. An image is …

Keyword Spotting (KWS) is here considered as a basic technology for Probabilistic Indexing
(PrIx) of large collections of handwritten text images to allow fast textual access to the …

There is a recent trend in handwritten text recognition with deep neural networks to replace
2D recurrent layers with 1D and in some cases even completely remove the recurrent layers …

This paper describes the system submitted by A2iA to the second Maurdor evaluation for
multi-lingual text recognition. A system based on recurrent neural networks and weighted …

This paper describes the second edition of the Handwritten Text Recognition (HTR) contest
on the tranScriptorium datasets that has been held in the context of the International …