Tomáš Skopal

1.4k citations
110 papers · 1.0k · h-index 18

Impact in

Papers in

Tomáš Skopal

101 papers receiving 953 citations

Peers

Tomáš Skopal
Comparison fields: 5 of 67
  • Signal Processing 524
  • Computer Vision and Pattern Recognition 641
  • Artificial Intelligence 313
  • Computer Networks and Communications 189
  • Management Information Systems 49
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Yuan‐Chi Chang United States
Marcos R. Vieira United States
Richard Connor United Kingdom
Davide Martinenghi Italy
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Alfonso F. Cárdenas United States
Panayiotis Bozanis Greece
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Citations per field
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Citations per year

Countries citing papers authored by Tomáš Skopal

Since Specialization
Citations

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

Fields of papers citing papers by Tomáš Skopal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200761
2 201155
3 201155
4
PM-tree: Pivoting Metric Tree for Similarity Search in Multimedia Databases.
200446
5 200537
6
Pivoting M-tree: A Metric Access Method for Efficient Similarity Search.
200435
7 200633
8 200632
9 201230
10 201425
11 200325
12 201224
13 201422
14 201122
15 201622
16 201122
17 200821
18 201120
19 200716
20 200816

About Tomáš Skopal

Tomáš Skopal is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 110 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (56 papers), Data Management and Algorithms (49 papers), Video Analysis and Summarization (38 papers), Image Retrieval and Classification Techniques (29 papers), Algorithms and Data Compression (15 papers), Advanced Database Systems and Queries (13 papers), Semantic Web and Ontologies (12 papers) and Data Mining Algorithms and Applications (6 papers). The work is most often cited by research in Signal Processing (524 citations), Computer Vision and Pattern Recognition (641 citations), Artificial Intelligence (313 citations), Computer Networks and Communications (189 citations) and Management Information Systems (49 citations). Tomáš Skopal has collaborated with scholars based in Czechia, Germany and Chile. Frequent co-authors include Jakub Lokoč, Benjamín Bustos, Václav Snåšel, Jaroslav Pokorný, Christian Beecks, David Hoksza, Michal Krátký, Magnus Lie Hetland, Thomas Seidl and Martin Nečaský. Their work appears in journals such as Lecture notes in computer science, Information Systems, Knowledge and Information Systems, Multimedia Tools and Applications and ACM Computing Surveys.

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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