Jiří Dvorský

431 citations
46 papers · 188 indexed · h-index 8
Topics
Data Management and Algorithms (7 papers)graph theory and CDMA systems (7 papers)Algorithms and Data Compression (6 papers)
Partner nations
CzechiaPolandNorway

In The Last Decade

Jiří Dvorský

40 papers receiving 171 citations

Peers

Jiří Dvorský
Comparison fields: 5 of 66
  • Artificial Intelligence 65
  • Electrical and Electronic Engineering 50
  • Information Systems 35
  • Computer Vision and Pattern Recognition 35
  • Materials Chemistry 28
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Citations per field
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Citations per year

Countries citing papers authored by Jiří Dvorský

Since Specialization
Citations

This map shows the geographic impact of Jiří Dvorský'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 Jiří Dvorský with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiří Dvorský more than expected).

Fields of papers citing papers by Jiří Dvorský

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiří Dvorský. 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 Jiří Dvorský. The network helps show where Jiří Dvorský may publish in the future.

Co-authorship network of co-authors of Jiří Dvorský

This figure shows the co-authorship network connecting the top 25 collaborators of Jiří Dvorský. A scholar is included among the top collaborators of Jiří Dvorský 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 Jiří Dvorský. Jiří Dvorský 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 10
2 26
3
Predicting PM 10 Concentrations Using Fuzzy Kriging.
4
4
Spatial Clustering of Disease Events Using Bayesian Methods.
1
5
On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic
1
6
P System Based Model of Passenger Flow in Public Transportation Systems: a Case Study of Prague Metro.
2
7
Unsupervised Algorithm for Post-Processing of Roughly Segmented Categorical Time Series
1
8
Combined Method for Effective Clustering based on Parallel SOM and Spectral Clustering.
3
9
Using SVM and Clustering Algorithmsin IDS Systems.
2
10
Optimizing the mathematical model for prediction of energy production in wind power plants
5
11
Evolving Quasigroups by Genetic Algorithms.
5
12 2
13 16
14 8
15
Improvement of Text Compression Parameters Using Cluster Analysis.
4
16
Aplication of New Method of Multi-Criteria Analysis
1
17
Multi-dimensional Sparse Matrix Storage ?
1
18
Query Expansion and Evolution of Topic in Information Retrieval Systems.
7
19 11
20
Term Indexing in Information Retrieval Systems.
1

About Jiří Dvorský

Jiří Dvorský is a scholar working on Artificial Intelligence, Signal Processing and Geometry and Topology, having authored 46 papers that have together received 188 indexed citations. Recurring topics across this work include Data Management and Algorithms (7 papers), graph theory and CDMA systems (7 papers) and Algorithms and Data Compression (6 papers). The work is most often cited by research in Geography, Planning and Development (13 citations), Signal Processing (23 citations) and Artificial Intelligence (65 citations). Jiří Dvorský has collaborated with scholars based in Czechia, Poland and Norway. Frequent co-authors include Václav Snåšel, Jan Martinovič, Lukáš Prokop, Stanislav Mišák, Ajith Abraham, Khalid Saeed, Jan Platoš, Pavel Praks, Vit Voženílek and Jaroslav Pokorný. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Engineering Applications of Artificial Intelligence.

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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