Multimedia information retrieval using fuzzy cluster-based model learning

Saeid Sattari, Adnan Yazici

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multimedia data, particularly digital videos, which contain various modalities (visual, audio, and text) are complex and time consuming to model, process, and retrieve. Therefore, efficient methods are required for retrieval of such complex data. In this paper, we propose a multimodal query level fusion approach using a fuzzy cluster-based learning method to improve the retrieval performance of multimedia data. Experimental results on a real dataset demonstrate that employing fuzzy clustering achieves notable improvement in the concept-based query retrieval performance.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509060344
DOIs
Publication statusPublished - Aug 23 2017
Event2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 - Naples, Italy
Duration: Jul 9 2017Jul 12 2017

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
CountryItaly
CityNaples
Period7/9/177/12/17

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ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Sattari, S., & Yazici, A. (2017). Multimedia information retrieval using fuzzy cluster-based model learning. In 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 [8015717] (IEEE International Conference on Fuzzy Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2017.8015717