J.J. van Hees

197 total papers · 1.0k total citations
21 papers, 520 citations indexed

About

J.J. van Hees is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, J.J. van Hees has authored 21 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 4 papers in Media Technology. Recurrent topics in J.J. van Hees's work include Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). J.J. van Hees is often cited by papers focused on Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). J.J. van Hees collaborates with scholars based in Germany, United States and Spain. J.J. van Hees's co-authors include Andreas Dengel, Federico Raue, Tobias Hinz, Ralf Biedert, Georg Buscher, Sven Schwarz, Damian Borth, Benjamin Bischke, Patrick Helber and Tim Althoff and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neural Networks and Earth system science data.

In The Last Decade

J.J. van Hees

20 papers receiving 498 citations

Hit Papers

Audioclip: Extending Clip... 2022 2026 2023 2024 2022 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
J.J. van Hees 247 140 93 89 40 21 520
Camilla Forsell 361 1.5× 107 0.8× 74 0.8× 64 0.7× 44 1.1× 33 504
Masahiro Takatsuka 330 1.3× 137 1.0× 67 0.7× 115 1.3× 37 0.9× 59 563
Geórgia Albuquerque 430 1.7× 150 1.1× 88 0.9× 107 1.2× 54 1.4× 31 534
Alejandro Betancourt 179 0.7× 69 0.5× 108 1.2× 24 0.3× 30 0.8× 19 460
Roger W. Ehrich 235 1.0× 141 1.0× 111 1.2× 14 0.2× 16 0.4× 43 521
Kevin T. McDonnell 258 1.0× 60 0.4× 64 0.7× 51 0.6× 40 1.0× 22 606
Ben Daubney 432 1.7× 75 0.5× 43 0.5× 39 0.4× 21 0.5× 12 532
Randy Sargent 181 0.7× 54 0.4× 142 1.5× 13 0.1× 32 0.8× 32 564
C. Mario Christoudias 390 1.6× 151 1.1× 41 0.4× 18 0.2× 28 0.7× 16 566
K. Sengupta 341 1.4× 118 0.8× 40 0.4× 121 1.4× 12 0.3× 33 495

Countries citing papers authored by J.J. van Hees

Since Specialization
Citations

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

Fields of papers citing papers by J.J. van Hees

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.J. van Hees

This figure shows the co-authorship network connecting the top 25 collaborators of J.J. van Hees. A scholar is included among the top collaborators of J.J. van Hees 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 J.J. van Hees. J.J. van Hees is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

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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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