Classifying polish in use-wear analysis with convolutional neural networks.

ABSTRACT: Lithic use-wear analysis examines micro- and macroscopic traces on tool surfaces resulting from human use and post-depositional processes. Polish, formed through surface abrasion with different materials, is a key diagnostic feature that is increasingly analyzed using machine learning to enhance automation and standardization. However, further research is needed to explore whether deep learning approaches, in particular, can be effectively applied to use-wear analysis and to determine the optimal surface area size (e.g., patch size and microscope objectives) and model architecture (custom vs. pre-trained) for achieving the best results. This study employs convolutional neural networks (CNNs) to classify experimental polish based on contact material (wood, hide, bone) and use intensity, whi

SUBMITTER: Eleftheriadou A 

PROVIDER: S-EPMC12546859 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature