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Appearance Meets Geometry: Deep Learning for Semantic Segmentation of Archaeological Fortification Masonry

descriptionPublicationkeyboard_double_arrow_right Preprint Under curation English Publisher:Zenodo
Authors: Schnorr, Nils; Leimkuehler, Thomas;

doi: 10.5281/zenodo.22642332

Appearance Meets Geometry: Deep Learning for Semantic Segmentation of Archaeological Fortification Masonry

Abstract

This is the preprint for a conference proceedings article to be submitted to the CAA 2025 proceedings. The title of the presentation held by Nils Schnorr during the 2025 conference was "Machine Learning in Archaeological Fortification Studies – A CNN-Based Approach for the Caria Region"

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