Matej Perše

557 citations
15 papers · 388 · h-index 9

Impact in

Papers in

Matej Perše

14 papers receiving 365 citations

Peers

Matej Perše
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 232
  • Media Technology 74
  • Orthopedics and Sports Medicine 56
  • Human-Computer Interaction 22
  • Biophysics 19
Replace Shih-Fu Chang with:
Shih-Fu Chang United States
Bastian Goldlücke Germany
Andreas Artemiou United Kingdom
Daniel González-Jiménez Spain
Giorgos Sfikas Greece
Richard Mann Canada
Jiann-Shu Lee Taiwan
Nicola Adami Italy
Yuanyuan Shang China
Matej Perše relative to Shih-Fu Chang United States Shih-Fu Chang's profile →
Citations per field
00.5×4.7×
Shih-Fu Chang · 1×
Citations per year

Countries citing papers authored by Matej Perše

Since Specialization
Citations

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

Fields of papers citing papers by Matej Perše

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Matej Perše, 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 Matej Perše Line = papers co-authored together Matej Perše links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 200897
2 200679
3 201056
4 200842
5 201227
6
AN ANALYSIS OF BASKETBALL PLAYERS' MOVEMENTS IN THE SLOVENIAN BASKETBALL LEAGUE PLAY-OFFS USING THE SAGIT TRACKING SYSTEM
200822
7 200518
8 200915
9 200510
10 20087
11 20114
12 20134
13 20154
14
Observing Human Motion Using Far-Infrared (FLIR) Camera - Some Preliminary Studies
20042
15
VIRTUAL FIELD TRIP AS TOOL FOR ENVIRONMENTAL EDUCATION
20121

About Matej Perše

Matej Perše is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Information Systems and Computational Mechanics, having authored 15 papers that have together received 388 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (4 papers), Time Series Analysis and Forecasting (4 papers), Video Analysis and Summarization (4 papers), Human Pose and Action Recognition (3 papers), Mobile Learning in Education (3 papers), Anomaly Detection Techniques and Applications (3 papers), Astronomical Observations and Instrumentation (2 papers) and Geography Education and Pedagogy (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (232 citations), Media Technology (74 citations), Orthopedics and Sports Medicine (56 citations), Human-Computer Interaction (22 citations) and Biophysics (19 citations). Matej Perše has collaborated with scholars based in Slovenia, Mozambique and Germany. Frequent co-authors include Matej Kristan, Janez Perš, Stanislav Kovačič, Goran Vučković, Andrej Šorgo, S. Kovacic, Gašper Mušič, Goran Vučković, Krištof Oštir and Tomaž Rodič. Their work appears in journals such as Pattern Recognition Letters, Computer Vision and Image Understanding, Pattern Recognition, Journal of Baltic Science Education and Problems of Education in the 21st Century.

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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