{"title":"Artificial Intelligence at the Interface between Cultural Heritage and Photography: A Systematic Literature Review","authors":"Carmen Silva, Lídia Oliveira","doi":"10.3390/heritage7070180","DOIUrl":null,"url":null,"abstract":"Artificial intelligence has inspired a significant number of studies on the interface between cultural heritage and photography. The aims of these studies are, among others, to streamline damage monitoring or diagnoses for heritage preservation, enhance the production of high-fidelity 3D models of cultural assets, or improve the analysis of heritage images using computer vision. This article presents the results of a systematic literature review to highlight the recent state of these studies, published in the last five years and available in the Scopus, Web of Science, and JSTOR databases. The aim is to identify the potential and challenges of artificial intelligence through the connection between cultural heritage and photography, the latter of which represents a relevant methodological aspect in these investigations. In addition to the advances exemplified, the vast majority of studies indicate that there are also many obstacles to overcome. In particular, there is a need to improve artificial intelligence methods that still have significant flaws. These include inaccuracy in the automatic classification of images and limitations in the applications of the results. This article also aims to reflect on the meaning of these innovations when considering the direction of the relationship between cultural heritage and photography.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":" 28","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/heritage7070180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence has inspired a significant number of studies on the interface between cultural heritage and photography. The aims of these studies are, among others, to streamline damage monitoring or diagnoses for heritage preservation, enhance the production of high-fidelity 3D models of cultural assets, or improve the analysis of heritage images using computer vision. This article presents the results of a systematic literature review to highlight the recent state of these studies, published in the last five years and available in the Scopus, Web of Science, and JSTOR databases. The aim is to identify the potential and challenges of artificial intelligence through the connection between cultural heritage and photography, the latter of which represents a relevant methodological aspect in these investigations. In addition to the advances exemplified, the vast majority of studies indicate that there are also many obstacles to overcome. In particular, there is a need to improve artificial intelligence methods that still have significant flaws. These include inaccuracy in the automatic classification of images and limitations in the applications of the results. This article also aims to reflect on the meaning of these innovations when considering the direction of the relationship between cultural heritage and photography.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.