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

Nowadays, there is a huge amount of Historical Arabic Documents (HAD) in the national
libraries and archives around the world. Analyzing this type of data manually is a difficult and …

In this paper we present an unsupervised segmentation-free method for spotting and
searching query, especially, for images documents in handwritten Arabic, for this …

Handwriting recognition is a research topic with a lot of challenges and complications. One
of the main complications is big databases that affect classifier complexities and their ability …

Automatic Recognition of Arabic Handwriting is a pervasive field that has many challenging
complications to solve. Such complications include big databases and complex computing …

Nowadays, access to Arabic historical documents has become easier and faster due to the
availability of digital copies of manuscripts. However, dealing with them manually remains …

The current paper gives an overview on the technologies used in word spotting especially
for handwritten documents. We present recent interesting published researches in this …

Old handwritten Arabic documents are part of the richest cultural heritage and contains a
wealth of information. The repetitive manipulation of these manuscripts should be avoided …

In this paper we present an unsupervised segmentation-free method for spotting and
searching query, especially, for images documents in handwritten Arabic, for this …

The offline handwritten text recognition is one of the most challenging tasks in document
image analysis; our aim is to recreate the cultural importance of the Kannada Language …