Abstract Handwritten Text Recognition is a important requirement in order to make visible
the contents of the myriads of historical documents residing in public and private archives …

This paper presents a systematic literature review of image datasets for document image
analysis, focusing on historical documents, such as handwritten manuscripts and early …

Nowadays, deep learning methods are employed in a broad range of research fields. The
analysis and recognition of historical documents, as we survey in this work, is not an …

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 …

Abstract Document Layout Analysis, which is the task of identifying different semantic
regions inside of a document page, is a subject of great interest for both computer scientists …

Historical palm-leaf manuscript and early paper documents from Indian subcontinent form
an important part of the world's literary and cultural heritage. Despite their importance, large …

The application of handwritten text recognition to historical works is highly dependant on
accurate text line retrieval. A number of systems utilizing a robust baseline detection …

High quality document layout analysis is fundamental to the accurate processing of
handwritten textual material, on both the level of individual lines and higher order zones …

We present a method for word spotting using convolutional siamese network. A
convolutional siamese network employs two identical convolutional network to rank …

OCR approaches have been widely advanced in recent years thanks to the resurgence of
deep learning. However, to the best of our knowledge, there is little work on Mongolian …