Analyzing the layout of a document to identify headers, sections, tables, figures etc. is critical
to understanding its content. Deep learning based approaches for detecting the layout …

We aim to investigate the performance of current OCR systems on low resource languages
and low resource scripts. We introduce and make publicly available a novel benchmark …

OCR errors are common in digitised historical archives significantly affecting their usability
and value. Generative Language Models (LMs) have shown potential for correcting these …

This study attempts the task of handwritten text recognition within the context of the Swedish
language. It examines the applicability of deep neural networks to comprehend handwritten …

In the past, computer vision systems for digitized documents could rely on systematically
captured, high-quality scans. Today, transactions involving digital documents are more likely …

Image Enhancement is a topic of key importance with a wide variety of uses, both for visual
perception and for follow on tasks like optical character recognition. This thesis explores two …