Historical Manuscript

Research on historical manuscripts focuses on developing advanced computational methods to analyze and transcribe these fragile and often challenging documents. Current efforts leverage deep learning architectures, including transformers, YOLO models, and Faster R-CNN, to improve Optical Character Recognition (OCR) accuracy, detect and recognize individual characters even in degraded or overlapping text (like palimpsests), and extract spatial information from textual descriptions. These advancements are significantly impacting historical research by enabling large-scale analysis of previously inaccessible archives, facilitating more accurate dating of manuscripts, and providing new tools for understanding the historical context embedded within these primary sources.