Petr Gajdoš

1.0k total citations
80 papers, 609 citations indexed

About

Petr Gajdoš is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Petr Gajdoš has authored 80 papers receiving a total of 609 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 18 papers in Signal Processing. Recurrent topics in Petr Gajdoš's work include Image Retrieval and Classification Techniques (9 papers), Data Management and Algorithms (8 papers) and Acute Lymphoblastic Leukemia research (7 papers). Petr Gajdoš is often cited by papers focused on Image Retrieval and Classification Techniques (9 papers), Data Management and Algorithms (8 papers) and Acute Lymphoblastic Leukemia research (7 papers). Petr Gajdoš collaborates with scholars based in Czechia, France and Armenia. Petr Gajdoš's co-authors include Václav Snåšel, Eva Kriegová, Miloš Kudělka, Zuzana Mikulková, Gayane Manukyan, Pavel Moravec, Tomáš Papajík, Jiří Gallo, Pavel Krömer and Kristína Kejlová and has published in prestigious journals such as Blood, Bioinformatics and Scientific Reports.

In The Last Decade

Petr Gajdoš

74 papers receiving 590 citations

Peers

Petr Gajdoš
Comparison fields: 5 of 136
  • Immunology 88
  • Molecular Biology 81
  • Artificial Intelligence 67
  • Rheumatology 63
  • Computer Vision and Pattern Recognition 62
Replace Jun Kato with:
Jun Kato Japan
Debasree Sarkar India
Lihong Ren China
Liang Qian China
Tony Kam‐Thong Switzerland
Hong Guo China
Zhao Zhi-gang China
Shimin Wang China
Jie Cai China
S. Amin United States
Jun Kato Japan View profile →
Citations per field, relative to Petr Gajdoš
Petr Gajdoš · 1×
Citations per year, relative to Petr Gajdoš
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Countries citing papers authored by Petr Gajdoš

Since Specialization
Citations

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

Fields of papers citing papers by Petr Gajdoš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Petr Gajdoš

This figure shows the co-authorship network connecting the top 25 collaborators of Petr Gajdoš. A scholar is included among the top collaborators of Petr Gajdoš 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 Petr Gajdoš. Petr Gajdoš 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
# Work Indexed citations
1 12
2 21
3 9
4 49
5 21
6 38
7 2
8 22
9
Human activity recognition: classifier performance evaluation on multiple datasets
4
10
Application and comparison of modified classifiers for human activity recognition
6
11
An Overview of Classification Techniques for Human Activity Recognition
3
12
Two-step Modified SOM for Parallel Calculation.
1
13 9
14
Using Matrix Decompositions in Formal Concept Analysis.
6
15
Process and Logic Approaches in the Intelligent Agents Behavior
2
16
Logic and Artificial Intelligence for Multi-Agent Systems
1
17
Vector model improvement by FCA and Topic Evolution
6
18
Usage of Genetic Algorithm for Lattice Drawing
4
19
Concept Lattice Generation by Singular Value Decomposition
12
20 12

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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