Computer Vision and Image Understanding

3.1k papers and 97.4k indexed citations i.

About

The 3.1k papers published in Computer Vision and Image Understanding in the last decades have received a total of 97.4k indexed citations. Papers published in Computer Vision and Image Understanding usually cover Computer Vision and Pattern Recognition (2.8k papers), Artificial Intelligence (452 papers) and Aerospace Engineering (449 papers) specifically the topics of Advanced Vision and Imaging (766 papers), Advanced Image and Video Retrieval Techniques (680 papers) and Video Surveillance and Tracking Methods (478 papers). The most active scholars publishing in Computer Vision and Image Understanding are Luc Van Gool, Tinne Tuytelaars, Andreas Ess, Herbert Bay, T.F. Cootes, D. H. Cooper, Chris Taylor, James Graham, Thomas B. Moeslund and Dariu M. Gavrila.

In The Last Decade

Fields of papers published in Computer Vision and Image Understanding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computer Vision and Image Understanding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Computer Vision and Image Understanding.

Countries where authors publish in Computer Vision and Image Understanding

Since Specialization
Citations

This map shows the geographic impact of research published in Computer Vision and Image Understanding. 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 papers published in Computer Vision and Image Understanding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computer Vision and Image Understanding more than expected).

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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