Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Selective Search for Object Recognition
20134.0k citationsJasper Uijlings, Koen E. A. van de Sande et al.International Journal of Computer Visionprofile →
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
2018960 citationsAlina Kuznetsova, Neil Alldrin et al.arXiv (Cornell University)profile →
COCO-Stuff: Thing and Stuff Classes in Context
2018693 citationsJasper Uijlings, Vittorio Ferrari et al.profile →
Segmentation as selective search for object recognition
2011480 citationsKoen E. A. van de Sande, Jasper Uijlings et al.UvA-DARE (University of Amsterdam)profile →
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
2018378 citationsAlina Kuznetsova, Neil Alldrin et al.arXiv (Cornell University)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Jasper Uijlings
Since
Specialization
Citations
This map shows the geographic impact of Jasper Uijlings'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 Jasper Uijlings with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jasper Uijlings more than expected).
This network shows the impact of papers produced by Jasper Uijlings. 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 Jasper Uijlings. The network helps show where Jasper Uijlings may publish in the future.
Co-authorship network of co-authors of Jasper Uijlings
This figure shows the co-authorship network connecting the top 25 collaborators of Jasper Uijlings.
A scholar is included among the top collaborators of Jasper Uijlings 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 Jasper Uijlings. Jasper Uijlings is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kuznetsova, Alina, Neil Alldrin, Jasper Uijlings, et al.. (2020). The Open Images Dataset V4. International Journal of Computer Vision. 128(7). 1956–1981.130 indexed citations
3.
Kuznetsova, Alina, Neil Alldrin, Jasper Uijlings, et al.. (2018). The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale. arXiv (Cornell University).960 indexed citations breakdown →
Yanulevskaya, Victoria, Jasper Uijlings, & Nicu Sebe. (2014). Learning to Group Objects. Institutional Research Information System (Università degli Studi di Trento). 3134–3141.15 indexed citations
Bruni, Elia, et al.. (2013). VSEM: An open library for visual semantics representation. Meeting of the Association for Computational Linguistics. 187–192.9 indexed citations
Uijlings, Jasper, et al.. (2013). Time matters!. Institutional Research Information System (Università degli Studi di Trento). 701–704.13 indexed citations
Sande, Koen E. A. van de, Jasper Uijlings, Theo Gevers, & A.W.M. Smeulders. (2011). Segmentation as selective search for object recognition. UvA-DARE (University of Amsterdam). 1879–1886.480 indexed citations breakdown →
Uijlings, Jasper, A.W.M. Smeulders, & Remko Scha. (2009). Real-time bag of words, approximately. UvA-DARE (University of Amsterdam). 1–8.58 indexed citations
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.