Handwritten document images can be highly affected by degradation for different reasons:
Paper ageing, daily-life scenarios (wrinkles, dust, etc.), bad scanning process and so on …

Recently, deep learning techniques demonstrated efficiency in building better performing
machine learning models which are required in the field of offline Arabic handwriting …

Recognition of cursive handwritten Arabic text is a difficult problem because of context-
sensitive character shapes, the non-uniform spacing between words and within a word …

Handwritten text recognition remains a popular area of research. An analysis of these
techniques is more necessary. This article is practically interested in a bibliographic study on …

The Transformer has quickly become the dominant architecture for various pattern
recognition tasks due to its capacity for long-range representation. However, transformers …

Abstract Arabic Handwritten Text Recognition (AHTR) based on deep learning approaches
remains a challenging problem due to the inevitable domain shift like the variability among …

Arabic handwriting recognition is considered among the most important and challenging
recognition research subjects due to the cursive nature of writing and the similarities …

One of the most recent challenging issues of pattern recognition and artificial intelligence is
Arabic text recognition. This research topic is still a pervasive and unaddressed research …

Abstract Today's Arabic Handwriting recognition systems are able to recognize arbitrary
words over a large but finite vocabulary. Systems operating with a fixed vocabulary are …

In recent years, Deep neural networks (DNNs) have achieved great success in sequence
modeling. Several deep models have been used for enhancing Handwriting Text …