Vedran Sabol

882 citations
58 papers · 467 indexed · h-index 12

Impact in

Papers in

Vedran Sabol

56 papers receiving 431 citations

Peers

Vedran Sabol
Comparison fields: 5 of 62
  • Computer Vision and Pattern Recognition 251
  • Artificial Intelligence 219
  • Information Systems 152
  • Signal Processing 69
  • Computer Science Applications 29
Replace Sana Malik with:
Sana Malik United States
Kai A. Olsen Norway
Roberto de Pinho Brazil
Anne Schur United States
M. Shahriar Hossain United States
Jae‐wook Ahn United States
Anselm Spoerri United States
Thomas Reichherzer United States
Óscar Sanjuán Martínez Spain
Wolfgang Kienreich Austria
Vedran Sabol relative to Sana Malik United States Sana Malik's profile →
Citations per field
00.5×1.5×
Sana Malik · 1×
Citations per year

Countries citing papers authored by Vedran Sabol

Since Specialization
Citations

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

Fields of papers citing papers by Vedran Sabol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20241
3 202411
4 20194
5 201712
6
uRank: Exploring Document Recommendations through an Interactive User-Driven Approach.
20159
7 20153
8
Automated Visualization Support for Linked Research Data
20137
9
Incremental and Scalable Computation of Dynamic Topography Information Landscapes
20123
10 201119
11
Visual Analyses on Linked Data – An Opportunity for both Fields
20111
12 20102
13
Knowledge Discovery using the Knowminer Framework
20098
14 200911
15 20081
16
Visualization Metaphors for Multi-modal Meeting Data.
20073
17 20052
18 20052
19
InfoSky: Visual Exploration of Large Hierarchical Document Repositories
20034
20 200224

About Vedran Sabol

Vedran Sabol is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Computer Science Applications and Information Systems, having authored 58 papers that have together received 467 indexed citations. Recurring topics across this work include Data Visualization and Analytics (34 papers), Semantic Web and Ontologies (16 papers), Video Analysis and Summarization (12 papers), Data Management and Algorithms (9 papers), Advanced Database Systems and Queries (8 papers), Image Retrieval and Classification Techniques (7 papers), Multimedia Communication and Technology (5 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (251 citations), Artificial Intelligence (219 citations), Information Systems (152 citations), Signal Processing (69 citations) and Computer Science Applications (29 citations). Vedran Sabol has collaborated with scholars based in Austria, Germany and Malaysia. Frequent co-authors include Michael Granitzer, Wolfgang Kienreich, Eduardo Veas, Keith Andrews, Klaus Tochtermann, Frank Kappe, Peter Auer, Dickson Lukose, Christin Seifert and Tobias Schreck. Their work appears in journals such as Future Internet, Scientific Reports, Information Visualization, Frontiers in Big Data and Big Data Research.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026