Semantic Segmentation of Archaeological Features on Public Lands: Case Study of Historical Cotton Terraces within the Piedmont National Wildlife Refuge, Georgia, USA

The logistics, costs, and capacity needed to complete extensive archaeological pedestrian surveys to inventory cultural resources present challenges to public land managers. To address these issues, we developed a workflow combining lidar-derived imagery and deep learning (DL) models tailored for cu...

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Bibliographic Details
Main Authors:	Claudine Gravel-Miguel, Grant Snitker, Jayde N. Hirniak, Katherine Peck, Alex Fetterhoff
Format:	Article
Language:	English
Published:	Cambridge University Press
Series:	Advances in Archaeological Practice
Subjects:	convolutional neural network (CNN) cultural resource management (CRM) deep learning lidar terraces U-Net red neuronal convolucional (RNC) programas de gestión de recursos culturales (PGRC) aprendizaje profundo terrazas
Online Access:	https://www.cambridge.org/core/product/identifier/S2326376825000014/type/journal_article
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Semantic Segmentation of Archaeological Features on Public Lands: Case Study of Historical Cotton Terraces within the Piedmont National Wildlife Refuge, Georgia, USA

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