Ancient languages preserve the cultures and histories of the past. However, their study is
fraught with difficulties, and experts must tackle a range of challenging text-based tasks, from …

This paper presents an end-to-end neural network system to identify writers through
handwritten word images, which jointly integrates global-context information and a …

Landmark-based human action recognition in videos is a challenging task in computer
vision. One key step is to design a generic approach that generates discriminative features …

Offline handwriting has become a very important part in the field of behavioral biometrics. In
this paper, we proposed an approach to identify writers from their handwritten documents …

Writer identification from handwriting samples has been an interesting research problem for
the pattern recognition community in general and handwriting recognition community in …

Determining the writer or transcriber of historical Arabic manuscripts has always been a
major challenge for researchers in the field of humanities. With the development of …

For the skeleton-based gesture recognition, graph convolutional networks (GCNs) have
achieved remarkable performance since the human skeleton is a natural graph. However …

Identifying the writer of a handwritten document has remained an interesting pattern
classification problem for document examiners, forensic experts, and paleographers. While …

Understanding handwritten documents is a vital and challenging problem that attracts many
researchers in the fields of forensic and authentication science. This paper presents an …

Writer identification form historical manuscripts presents a challenging problem with
significant implications for understanding the authorship of ancient texts. In this paper, we …