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Journal of Mathematical and Computational Science ISSN 1927-5307 (Print)

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J. Math. Comput. Sci. 12 (2022), Article ID 96

Asymmetry quantification in cross modal retrieval using copulas

Loubna Karbil, Mohamed El Maazouz, Ahmed Sani, Imane Daoudi

PDF (156.5 KB) https://doi.org/10.28919/jmcs/6951

Abstract

Copulas are used to describe and explain the asymmetry between image-text and text-image retrieval observed in different values of the mean average precision (MAP). We use empirical copulas to quantify the asymmetry in a general framework of cross-modal retrieval via suitable asymmetry measures. Several experiments are done on real world dataset feautures to prove the relevance of our analysis.

Published
23 February 2022
Volume
12 (2022)
License
CC BY 3.0

Copyright © 2022 Loubna Karbil, Mohamed El Maazouz, Ahmed Sani, Imane Daoudi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article

L. Karbil, M. E. Maazouz, A. Sani, I. Daoudi, Asymmetry quantification in cross modal retrieval using copulas, J. Math. Comput. Sci. 12 (2022), 96. https://doi.org/10.28919/jmcs/6951

BibTeX
@article{Karbil2022,
  author  = {Karbil, Loubna and Maazouz, Mohamed El and Sani, Ahmed and Daoudi, Imane},
  title   = {Asymmetry quantification in cross modal retrieval using copulas},
  journal = {J. Math. Comput. Sci.},
  volume  = {12},
  year    = {2022},
  pages   = {96},
  doi     = {10.28919/jmcs/6951}
}