{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T01:46:13Z","timestamp":1782524773666,"version":"3.54.5"},"reference-count":44,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T00:00:00Z","timestamp":1669766400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>In the last few years, the spreading of new technologies, such as augmented reality (AR), has been changing our way of life. Notably, AR technologies have different applications in the cultural heritage realm, improving available information for a user while visiting museums, art exhibits, or generally a city. Moreover, the spread of new and more powerful mobile devices jointly with virtual reality (VR) visors contributes to the spread of AR in cultural heritage. This work presents an augmented reality mobile system based on content-based image analysis techniques and linked open data to improve user knowledge about cultural heritage. In particular, we explore the uses of traditional feature extraction methods and a new way to extract them employing deep learning techniques. Furthermore, we conduct a rigorous experimental analysis to recognize the best method to extract accurate multimedia features for cultural heritage analysis. Eventually, experiments show that our approach achieves good results with respect to different standard measures.<\/jats:p>","DOI":"10.3390\/computers11120172","type":"journal-article","created":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T02:21:57Z","timestamp":1669774917000},"page":"172","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["An Augmented Reality CBIR System Based on Multimedia Knowledge Graph and Deep Learning Techniques in Cultural Heritage"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7003-4781","authenticated-orcid":false,"given":"Antonio M.","family":"Rinaldi","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Via Claudio, 21, 80125 Napoli, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8732-1733","authenticated-orcid":false,"given":"Cristiano","family":"Russo","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Via Claudio, 21, 80125 Napoli, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9763-8745","authenticated-orcid":false,"given":"Cristian","family":"Tommasino","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Via Claudio, 21, 80125 Napoli, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"27447","DOI":"10.1007\/s11042-018-5931-7","article-title":"Multimedia and geographic data integration for cultural heritage information retrieval","volume":"77","author":"Purificato","year":"2018","journal-title":"Multimedia Tools Appl."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Purificato, E., and Rinaldi, A.M. 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