A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features
In recent years the information user needs have been changed due to the heterogeneity of web contents which increasingly involve in multimedia contents. Although modern search engines provide visual queries, it is not easy to find systems that allow searching from a particular domain of interest and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/12/11/183 |
| _version_ | 1797549575353925632 |
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| author | Antonio Maria Rinaldi Cristiano Russo Cristian Tommasino |
| author_facet | Antonio Maria Rinaldi Cristiano Russo Cristian Tommasino |
| author_sort | Antonio Maria Rinaldi |
| collection | DOAJ |
| description | In recent years the information user needs have been changed due to the heterogeneity of web contents which increasingly involve in multimedia contents. Although modern search engines provide visual queries, it is not easy to find systems that allow searching from a particular domain of interest and that perform such search by combining text and visual queries. Different approaches have been proposed during years and in the semantic research field many authors proposed techniques based on ontologies. On the other hand, in the context of image retrieval systems techniques based on deep learning have obtained excellent results. In this paper we presented novel approaches for image semantic retrieval and a possible combination for multimedia document analysis. Several results have been presented to show the performance of our approach compared with literature baselines. |
| first_indexed | 2024-03-10T15:17:31Z |
| format | Article |
| id | doaj.art-19540c16e06e4a57b19cd26ed0e9296a |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-10T15:17:31Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-19540c16e06e4a57b19cd26ed0e9296a2023-11-20T18:47:34ZengMDPI AGFuture Internet1999-59032020-10-01121118310.3390/fi12110183A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep FeaturesAntonio Maria Rinaldi0Cristiano Russo1Cristian Tommasino2Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, ItalyDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, ItalyDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, ItalyIn recent years the information user needs have been changed due to the heterogeneity of web contents which increasingly involve in multimedia contents. Although modern search engines provide visual queries, it is not easy to find systems that allow searching from a particular domain of interest and that perform such search by combining text and visual queries. Different approaches have been proposed during years and in the semantic research field many authors proposed techniques based on ontologies. On the other hand, in the context of image retrieval systems techniques based on deep learning have obtained excellent results. In this paper we presented novel approaches for image semantic retrieval and a possible combination for multimedia document analysis. Several results have been presented to show the performance of our approach compared with literature baselines.https://www.mdpi.com/1999-5903/12/11/183content base image retrievalsemantic information retrievaldeep featuresmultimedia document retrieval |
| spellingShingle | Antonio Maria Rinaldi Cristiano Russo Cristian Tommasino A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features Future Internet content base image retrieval semantic information retrieval deep features multimedia document retrieval |
| title | A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features |
| title_full | A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features |
| title_fullStr | A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features |
| title_full_unstemmed | A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features |
| title_short | A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features |
| title_sort | knowledge driven multimedia retrieval system based on semantics and deep features |
| topic | content base image retrieval semantic information retrieval deep features multimedia document retrieval |
| url | https://www.mdpi.com/1999-5903/12/11/183 |
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