Research in offline Arabic handwriting recognition has increased considerably in the past
few years. This is evident from the numerous research results published recently in major …

Breast cancer is the most frequently diagnosed cancer in women worldwide and the leading
cause of cancer death among females. Currently the most effective method for early …

Segmenting arabic manuscripts into text-lines and words is an important step to make
recognition systems more efficient and accurate. The major problem making this task crucial …

In this paper, we propose using a convolutional neural network (CNN) in the recognition of
Arabic handwritten literal amounts. Deep convolutional neural networks have achieved an …

The first observation concerning Arabian manuscript reveals the complexity of the task,
especially for the used classifiers ensemble. One of the most important steps in the design of …

Due to the nature of handwriting with high degree of variability and imprecision, obtaining
features that represent words is a difficult task. In this research, a features extraction method …

Security of sensitive information at the time of transmission over public channels is one of
the critical issues in digital society. The DNA-based cryptography technique is a new …

In this paper, a new recognition system for off-line Arabic handwritten words is presented.
The proposed system uses for the first time scale invariant feature transform (SIFT) …

The aim of our work is to present a new method based on structural characteristics and a
fuzzy classifier for off-line recognition of handwritten Arabic characters in all their forms …

Arabic handwriting word recognition is a challenging problem due to Arabic's connected
letter forms, consonantal diacritics and rich morphology. One way to improve the recognition …