Håkan Ardö

31 papers receiving 395 citations

Peers

Håkan Ardö
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 173
  • Small Animals 99
  • Animal Science and Zoology 76
  • Safety, Risk, Reliability and Quality 55
  • Control and Systems Engineering 55
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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-authorship network of co-authors of Håkan Ardö

This figure shows the co-authorship network connecting the top 25 collaborators of Håkan Ardö. A scholar is included among the top collaborators of Håkan Ardö based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Håkan Ardö. Håkan Ardö is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 2
3
A Framework for Automated Traffic Safety Analysis from Video Using Modern Computer Vision
4
4 31
5 17
6 1
7 14
8 40
9 54
10
Public video data set for road transportation applications
10
11
Learning Based Image Segmentation of Pigs in a Pen
2
12
Enhancements of traffic micro simulation models using video analysis
2
13 45
14
Collection of Microlevel Safety and Efficiency Indicators with Automated Video Analysis
3
15 35
16
Online Viterbi Optimisation for Simple Event Detection in Video
4
17
Multi Sensor Loitering Detection Using Online Viterbi
5
18
Automated video analysis as a tool for analysing road user behaviour
8
19 26
20
Use of learning for detection and tracking of vehicles
1

About Håkan Ardö

Håkan Ardö is a scholar working on Computer Vision and Pattern Recognition, Small Animals and Developmental Biology, 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) and Advanced Image and Video Retrieval Techniques (8 papers). The work is most often cited by research in Small Animals (99 citations), Computer Vision and Pattern Recognition (173 citations) and Animal Science and Zoology (76 citations). Håkan Ardö has collaborated with scholars based in Sweden, United Kingdom and Denmark. Frequent co-authors include Kalle Åström, Anders Herlin, Viktor Öwall, Aliaksei Laureshyn, Markus Nilsson, C. Fred Bergsten, Paolo Rocco, Gianni Ferretti, Luca Bascetta and Herman Bruyninckx. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, Computers and Electronics in Agriculture and Journal of Vision.

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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