Handwritten Text Recognition (HTR) is essential for digitizing historical documents in
different kinds of archives. In this study, we introduce a hybrid form archive written in French …

Handwritten document images can be highly affected by degradation for different reasons:
Paper ageing, daily-life scenarios (wrinkles, dust, etc.), bad scanning process and so on …

Handwritten text recognition (HTR) has seen significant advancements in recent years,
mainly due to the incorporation of deep learning techniques. One area of HTR that has …

Despite the transition to digital information exchange, many documents, such as invoices,
taxes, memos and questionnaires, historical data, and answers to exam questions, still …

Abstract Handwritten Text Recognition (HTR) systems have gained interest in fields of
academic research and commercial applications. Deep learning techniques, and more …

In this study, a novel technique is proposed to recognize printed text in images for Urdu, a
low-resource language with a scarcity of benchmark datasets. The proposed technique is …

The recent advancements in the field of Artificial Intelligence (AI) translated to an increased
adoption of AI technology in the humanities, which is often challenged by the limited amount …

Offline handwritten text recognition (HTR) for historical documents aims for effective
transcription by addressing challenges that originate from the low quality of manuscripts …

Automatic handwriting recognition systems are of interest for academic research fields and
for commercial applications. Recent advances in deep learning techniques have shown …

Abstract Handwritten Document Recognition (HDR) has emerged as a challenging task
integrating text and layout information recognition to tackle manuscripts end-to-end. Despite …