Iveta Dirgová Ľuptáková

402 citations
18 papers · 200 · h-index 5

Impact in

Papers in

Iveta Dirgová Ľuptáková

14 papers receiving 194 citations

Peers

Iveta Dirgová Ľuptáková
Comparison fields: 5 of 80
  • Computer Vision and Pattern Recognition 100
  • Artificial Intelligence 65
  • Computer Networks and Communications 41
  • Human-Computer Interaction 7
  • Statistical and Nonlinear Physics 14
Replace Muhammad Haseeb Arshad with:
Muhammad Haseeb Arshad Saudi Arabia
Vishal Bharti India
Hanhua Chen China
Feng-Tso Sun United States
Mathias Stäger Switzerland
Yufan Wang China
Kimin Lee South Korea
Meng Xing China
Pierre Morizet‐Mahoudeaux France
Iveta Dirgová Ľuptáková relative to Muhammad Haseeb Arshad Saudi Arabia Muhammad Haseeb Arshad's profile →
Citations per field
00.5×1.7×
Muhammad Haseeb Arshad · 1×
Citations per year

Countries citing papers authored by Iveta Dirgová Ľuptáková

Since Specialization
Citations

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

Fields of papers citing papers by Iveta Dirgová Ľuptáková

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iveta Dirgová Ľuptáková. 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 Iveta Dirgová Ľuptáková. The network helps show where Iveta Dirgová Ľuptáková may publish in the future.

Co-authors

The 7 scholars most cited alongside Iveta Dirgová Ľuptáková, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Iveta Dirgová Ľuptáková Line = papers co-authored together Iveta Dirgová Ľuptáková links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2022129
2 202220
3 201913
4 201712
5 20166
6 20154
7 20234
8 20143
9 20233
10 20242
11 20191
12 20141
13 20181
14 20231
15 20240
16 20250
17 20250
18 20240

About Iveta Dirgová Ľuptáková

Iveta Dirgová Ľuptáková is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 18 papers that have together received 200 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (4 papers), Anomaly Detection Techniques and Applications (3 papers), Advanced Clustering Algorithms Research (2 papers), Network Security and Intrusion Detection (2 papers), Reinforcement Learning in Robotics (2 papers), Online Learning and Analytics (2 papers), Petri Nets in System Modeling (1 paper) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (100 citations), Artificial Intelligence (65 citations), Computer Networks and Communications (41 citations), Human-Computer Interaction (7 citations) and Statistical and Nonlinear Physics (14 citations). Iveta Dirgová Ľuptáková has collaborated with scholars based in Slovakia, Bulgaria and Serbia. Frequent co-authors include Jiřı́ Pospı́chal, Ladislav Huraj, Георги Димитров, Dragan Stojanović, Aleksandra Kłos-Witkowska, Marko Milojković and Marcin Bernaś. Their work appears in journals such as Sensors, Applied Sciences, Emerging Science Journal, Mathematical Problems in Engineering and Brno University of Technology Digital Library (Brno University of Technology).

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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