Archaeological Research

Archaeological research is increasingly leveraging advanced computational methods to analyze and interpret data, aiming to improve efficiency and extract deeper insights from artifacts and sites. Current research focuses on applying deep learning, particularly semantic segmentation models, to analyze LiDAR data and satellite imagery for site detection and object identification, often employing transfer learning to address data scarcity. These techniques, while showing promise, highlight the importance of careful visualization selection and data annotation strategies for optimal performance. The integration of human expertise remains crucial for validating model outputs and ensuring the responsible application of these powerful tools.