Olga Kurasova

1.1k citations
70 papers · 613 indexed · h-index 14
Topics
Neural Networks and Applications (16 papers)Data Mining Algorithms and Applications (8 papers)Data Visualization and Analytics (7 papers)
Journals
SHILAP Revista de lepidopterologíaEuropean Journal of Operational ResearchIEEE Access
Partner nations
LithuaniaBulgariaCzechia

In The Last Decade

Olga Kurasova

66 papers receiving 583 citations

Peers

Olga Kurasova
Comparison fields: 5 of 129
  • Artificial Intelligence 275
  • Computer Vision and Pattern Recognition 159
  • Computational Theory and Mathematics 86
  • Information Systems 68
  • Signal Processing 60
Replace Gintautas Dzemyda with:
Gintautas Dzemyda Lithuania
Peter Malík Slovakia
Kilian Stoffel Switzerland
Don‐Lin Yang Taiwan
Qingchen Zhang China
Adamu Abubakar Malaysia
Xuemin Zhang China
José Palma Spain
Boris Kovalerchuk United States
Qiuming Zhu United States
Olga Kurasova relative to Gintautas Dzemyda Lithuania Gintautas Dzemyda's profile →
Citations per field
00.5×1.5×2.5×
Gintautas Dzemyda · 1×
Citations per year

Countries citing papers authored by Olga Kurasova

Since Specialization
Citations

This map shows the geographic impact of Olga Kurasova's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Olga Kurasova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olga Kurasova more than expected).

Fields of papers citing papers by Olga Kurasova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olga Kurasova. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Olga Kurasova. The network helps show where Olga Kurasova may publish in the future.

Co-authorship network of co-authors of Olga Kurasova

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Kurasova. A scholar is included among the top collaborators of Olga Kurasova based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Olga Kurasova. Olga Kurasova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 4
4 1
5 2
6 4
7 3
8 15
9 11
10 19
11 1
12 4
13 2
14 1
15 10
16 31
17
A Decision Support System for Solving Multiple Criteria Optimization Problems
2
18 25
19 1
20 2

About Olga Kurasova

Olga Kurasova is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 70 papers that have together received 613 indexed citations. Recurring topics across this work include Neural Networks and Applications (16 papers), Data Mining Algorithms and Applications (8 papers) and Data Visualization and Analytics (7 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Computer Vision and Pattern Recognition (159 citations) and Signal Processing (60 citations). Olga Kurasova has collaborated with scholars based in Lithuania, Bulgaria and Czechia. Frequent co-authors include Gintautas Dzemyda, Pavel Stefanovič, Ernestas Filatovas, Julius Žilinskas, Virginijus Marcinkevičius, Jolita Bernatavičienė, Karthik Sindhya, Povilas Treigys, Bożena Kostek and В. С. Медведев. Their work appears in journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and IEEE Access.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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