The rising popularity of deep learning can largely be attributed to the big data phenomenon,
the surge in the development of new and novel deep neural network architectures, and the …

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 …

Recently, with the outstanding performance of the transformer in NLP, approaches that
employ the transformer to address vision problem is becoming a research focus. However …

Identifying and verifying the identity of people based on scanned images of handwritten
documents is an applicable biometric modality with applications in forensic and historic …

Generating synthetic images of handwritten text in a writer-specific style is a challenging
task, especially in the case of unseen styles and new words, and even more when these …

The work focuses on the development of an adaptive technique for the physical interaction
handling between a human and a robot, as well as its experimental validation. The …

In this work, we explore massive pre-training on synthetic word images for enhancing the
performance on four benchmark downstream handwriting analysis tasks. To this end, we …

Writer identification based on handwriting recognition is considered one of the most
common research areas in pattern recognition and biometrics. It has attracted much …

Handwriting-based identification is a fundamental pattern recognition problem that has
attracted considerable interest in recent years. Writer identification is a major challenge …

Since the dawn of civilization, handwriting has been one of the most important forms of
communication. However, as handwriting differs from person to person, writer identification …