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 …

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

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 …

In recent years, Deep Learning models have become indispensable in several fields such
as computer vision, automatic object recognition, and automatic natural language …

The paper describes an approach towards road sign detection and recognition system. The
model consists of two parts: localization and recognition. First one is responsible for the …

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

Abstract Convolutional Neural Networks (CNNs) show state-of-the-art performance in
handwritten word recognition. Existing CNNs operate on one language and their accuracy …

In recent years, ensemble learning methods show great effectiveness in improving model
performance in several applications. Ensemble techniques rely on the incorporation of …

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

Deep learning models are considered a revolutionary learning paradigm in artificial
intelligence and machine learning, piquing the interest of image recognition and computer …