Jan Holub

64 papers receiving 293 citations

Peers

Jan Holub
Comparison fields: 5 of 76
  • Human-Computer Interaction 32
  • Computer Vision and Pattern Recognition 88
  • Signal Processing 42
  • Computer Graphics and Computer-Aided Design 12
  • Computer Networks and Communications 54
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Ron van Schyndel Australia
Benjamín Hernández Mexico
Xiangdong Li China
R.S. Rajesh India
Dominique Vaufreydaz France
Long Qin China
Rebeca Marfil Spain
Seop Hyeong Park South Korea
Syed Hasan Adil Pakistan
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Citations per field
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Citations per year

Countries citing papers authored by Jan Holub

Since Specialization
Citations

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

Fields of papers citing papers by Jan Holub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Holub, 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 Jan Holub Line = papers co-authored together Jan Holub links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Fusing Self-Reported and Sensor Data from Mixed-Reality Training
201425
2 202219
3 201714
4 201813
5 201612
6 202311
7 201610
8 201110
9 20189
10 20129
11 20159
12 20009
13 20038
14 20177
15 20077
16 20167
17 20206
18 20046
19 20156
20
OSCILLOSCOPE TESTING BY MEANS OF STOCHASTIC SIGNAL
20016

About Jan Holub

Jan Holub is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, Artificial Intelligence and Computational Mechanics, having authored 77 papers that have together received 318 indexed citations. Recurring topics across this work include Speech and Audio Processing (17 papers), Advanced Data Compression Techniques (12 papers), Sensor Technology and Measurement Systems (9 papers), Advanced Adaptive Filtering Techniques (9 papers), Wireless Communication Networks Research (6 papers), Transportation Systems and Safety (4 papers), Analog and Mixed-Signal Circuit Design (4 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Human-Computer Interaction (32 citations), Computer Vision and Pattern Recognition (88 citations), Signal Processing (42 citations), Computer Graphics and Computer-Aided Design (12 citations) and Computer Networks and Communications (54 citations). Jan Holub has collaborated with scholars based in Czechia, United States and Slovakia. Frequent co-authors include Eliot Winer, Hakob Avetisyan, Stephen B. Gilbert, Jan Fischer, Peter Počta, Michael C. Dorneich, Noah A. Smith, Rafael Radkowski, F. N. Thompson and Anne M. Sinatra. Their work appears in journals such as Measurement, Computer Standards & Interfaces, Scientific Reports, IEEE Access and IEEE Transactions on Instrumentation and Measurement.

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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