Deciphering the past: enhancing Assyrian Cuneiform recognition with YOLOv8 object detection

Cuneiform writing offers insight into our distant past. Emerging in the latter part of the 4th millennium BCE, cuneiform script is among the earliest known writing systems, alongside Egyptian hieroglyphs. It is believed to have originated with the Sumerians in southern Mesopotamia. Used for nearly three thousand years, it was eventually replaced by more accessible alphabet-based systems. Cuneiform texts were inscribed on various materials, but clay tablets were preferred due to their availability. Over 500,000 cuneiform documents have been found, with many yet to be analyzed by philologists. This highlights the need for effective methods to study the extensive cuneiform writings, traditionally examined manually. Deciphering ancient tablets is time-consuming, requiring extensive expertise. Signs on Assyrian cuneiform tablets were aimed to be detected in this study using the YOLOv8 object detection pretraining model. About 900 images of Assyrian tablets from the Iraq Museum were compiled and expanded to over 2000 through preprocessing and augmentation. This led to the identification of 11 new Assyrian references, with a mean average precision (mAP) at 50% of 82.7%, a precision of 71.3%, and a recall of 85.6% being achieved. The detection of cuneiform signs, as well as the selection and pronunciation of the modern Assyrian dialect, was facilitated by this research, aiding researchers in reading with a pre-trained model.