Artificial Intelligence and Decision Making
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Guidelines for authors

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS


Artificial Intelligence and Decision Making:
Year:
Volume:
Issue:
Page:
Find




Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register

Artificial Intelligence and Decision Making, 2021, Issue 1, Pages 86–97
DOI: https://doi.org/10.14357/20718594210108 (Mi iipr94) 		 
This article is cited in 1 scientific paper (total in 1 paper)

Analysis of signals, audio and video information

Assessing creativity using image analysis with neural networks

I. L. Uglanova, Y. S. Gelver, S. V. Tarasov, D. A. Gracheva, E. E. Vyrva

HSE University, Moscow, Russia
Full-text PDF (680 kB) Citations (1)
DOI: https://doi.org/10.14357/20718594210108
Abstract: The present study investigated the possibilities of assessing student creativity based on neural networks approaches for image analysis. The use of psychometric data analysis in the methodology of Latent Class Analysis (LCA) allowed us to obtain data labels to train the neural network without experts’ involvement. The high accuracy in network predictions for identifying image creativity suggested large-scale prospects for machine learning to assess complex educational and psychological characteristics.
Keywords: creativity, image analysis, neural networks, educational assessment, psychometrics, machine learning.
Funding agency Grant number
Russian Foundation for Basic Research 19-29-14110
English version:
Scientific and Technical Information Processing, 2022, Volume 49, Issue 5, Pages 371–378
DOI: https://doi.org/10.3103/S0147688222050124
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: I. L. Uglanova, Y. S. Gelver, S. V. Tarasov, D. A. Gracheva, E. E. Vyrva, “Assessing creativity using image analysis with neural networks”, Artificial Intelligence and Decision Making, 2021, no. 1, 86–97; Scientific and Technical Information Processing, 49:5 (2022), 371–378
Citation in format AMSBIB
\Bibitem{UglGelTar21}
\by I.~L.~Uglanova, Y.~S.~Gelver, S.~V.~Tarasov, D.~A.~Gracheva, E.~E.~Vyrva
\paper Assessing creativity using image analysis with neural networks
\jour Artificial Intelligence and Decision Making
\yr 2021
\issue 1
\pages 86--97
\mathnet{http://mi.mathnet.ru/iipr94}
\crossref{https://doi.org/10.14357/20718594210108}
\elib{https://elibrary.ru/item.asp?id=45149132}
\transl
\jour Scientific and Technical Information Processing
\yr 2022
\vol 49
\issue 5
\pages 371--378
\crossref{https://doi.org/10.3103/S0147688222050124}
Linking options:
  • https://www.mathnet.ru/eng/iipr94
  • https://www.mathnet.ru/eng/iipr/y2021/i1/p86
    • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Artificial Intelligence and Decision Making
    Statistics & downloads:
    Abstract page:20
    Full-text PDF :25
    References:1
     
      Contact us:
    		  Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024