Research on Identification, Evaluation, and Digitization of Historical Buildings Based on Deep Learning Algorithms: A Case Study of Quanzhou World Cultural Heritage Site

Abstract

Historical buildings have important historical and social value, but they are generally difficult to identify, complicated to evaluate, and insufficiently addressed in digitization research. On 25 July 2021, Quanzhou successfully applied for World Heritage status. In this case study, Qiaonan Village in the Quanzhou World Heritage Area is selected, and a deep learning algorithm is proposed for the identification, evaluation, and digitization of historical buildings. By comparing multiple models, the optimal model is selected for intelligent identification and classification of building elevations. Combined with GIS, a distribution map of the village buildings is created for digitization research. An intelligent monitoring platform is built to enable dynamic monitoring and hierarchical protection of the buildings, aiding in the protection of historical structures and the sustainable development of the tourism industry. In the future, we will continue to optimize the integration of YOLO and GIS and explore a more universal model for the intelligent protection of historical buildings.