Gertjan J. Burghouts

2.1k citations
57 papers · 1.4k indexed · 1 hit paper · h-index 13

Gertjan J. Burghouts

53 papers receiving 1.2k citations

Hit Papers

The Amsterdam Library of Object Images20042026201120182004100200300400500

Peers

Gertjan J. Burghouts
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 999
  • Artificial Intelligence 438
  • Media Technology 166
  • Aerospace Engineering 145
  • Signal Processing 130
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Andreas Savakis United States
Yangyu Fan China
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Gertjan J. Burghouts relative to Andreas Savakis United States Andreas Savakis's profile →
Citations per field
00.5×1.7×
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Citations per year

Countries citing papers authored by Gertjan J. Burghouts

Since Specialization
Citations

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

Fields of papers citing papers by Gertjan J. Burghouts

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gertjan J. Burghouts. 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 Gertjan J. Burghouts. The network helps show where Gertjan J. Burghouts may publish in the future.

Co-authorship network of co-authors of Gertjan J. Burghouts

This figure shows the co-authorship network connecting the top 25 collaborators of Gertjan J. Burghouts. A scholar is included among the top collaborators of Gertjan J. Burghouts 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 Gertjan J. Burghouts. Gertjan J. Burghouts 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 1
2 1
3 0
4
Hybrid ai: White paper
1
5 5
6 43
7 2
8 19
9 7
10
Action recognition by layout, selective sampling and soft-assignment
2
11 9
12 8
13 11
14
Correlations Between 48 Human Actions Improve Their Detection
12
15
Learning the fusion of audio and video aggression assessment by meta-information from human annotations
10
16
A Neural-Symbolic Cognitive Agent with a Mind's Eye
5
17 12
18
The Distribution Family of Similarity Distances
18
19 10
20
An Action Selection Architecture for an Emotional Agent
6

About Gertjan J. Burghouts

Gertjan J. Burghouts is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 57 papers that have together received 1.4k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (24 papers), Anomaly Detection Techniques and Applications (23 papers) and Video Surveillance and Tracking Methods (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (999 citations), Media Technology (166 citations) and Artificial Intelligence (438 citations). Gertjan J. Burghouts has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Jan‐Mark Geusebroek, A.W.M. Smeulders, Klamer Schutte, Iulia Lefter, Léon Rothkrantz, Henri Bouma, Judith Dijk, Pieter T. Eendebak, Jan Baan and Sebastiaan P. van den Broek. Their work appears in journals such as IEEE Transactions on Image Processing, International Journal of Computer Vision and Pattern Recognition Letters.

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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