Håkan Ardö

646 citations
32 papers · 417 · h-index 11

Impact in

Papers in

Håkan Ardö

31 papers receiving 395 citations

Peers

Håkan Ardö
Comparison fields: 5 of 75
  • Small Animals 99
  • Computer Vision and Pattern Recognition 173
  • Animal Science and Zoology 76
  • Safety, Risk, Reliability and Quality 55
  • Human-Computer Interaction 20
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Daihee Park South Korea
Yangyang Guo China
Niall O’Mahony Ireland
Qifan Wang United States
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Citations per field
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Citations per year

Countries citing papers authored by Håkan Ardö

Since Specialization
Citations

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

Fields of papers citing papers by Håkan Ardö

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201554
2 201145
3 200943
4 201640
5 200835
6 201831
7 200526
8 201123
9 201717
10 201614
11
Public video data set for road transportation applications
201410
12 200710
13 200610
14
Automated video analysis as a tool for analysing road user behaviour
20068
15 20126
16 20225
17
Multi Sensor Loitering Detection Using Online Viterbi
20075
18 20095
19
Online Viterbi Optimisation for Simple Event Detection in Video
20074
20
A Framework for Automated Traffic Safety Analysis from Video Using Modern Computer Vision
20194

About Håkan Ardö

Håkan Ardö is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Small Animals, Automotive Engineering and Control and Systems Engineering, having authored 32 papers that have together received 417 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (14 papers), Anomaly Detection Techniques and Applications (9 papers), Advanced Image and Video Retrieval Techniques (8 papers), Advanced Vision and Imaging (5 papers), Autonomous Vehicle Technology and Safety (4 papers), Animal Behavior and Welfare Studies (4 papers), Effects of Environmental Stressors on Livestock (3 papers) and Industrial Vision Systems and Defect Detection (2 papers). The work is most often cited by research in Small Animals (99 citations), Computer Vision and Pattern Recognition (173 citations), Animal Science and Zoology (76 citations), Safety, Risk, Reliability and Quality (55 citations) and Human-Computer Interaction (20 citations). Håkan Ardö has collaborated with scholars based in Sweden, United Kingdom and China. Frequent co-authors include Kalle Åström, Anders Herlin, Viktor Öwall, Aliaksei Laureshyn, C. Fred Bergsten, Markus Nilsson, Gianni Ferretti, Herman Bruyninckx, Eric Demeester and Luca Bascetta. Their work appears in journals such as ACM SIGPLAN Notices, animal, Journal of Vision, Computers and Electronics in Agriculture and IEEE Transactions on Circuits and Systems for Video Technology.

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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