Machine Vision and Applications

2.8k papers and 33.8k indexed citations i.

About

The 2.8k papers published in Machine Vision and Applications in the last decades have received a total of 33.8k indexed citations. Papers published in Machine Vision and Applications usually cover Computer Vision and Pattern Recognition (2.2k papers), Aerospace Engineering (433 papers) and Artificial Intelligence (378 papers) specifically the topics of Advanced Vision and Imaging (574 papers), Video Surveillance and Tracking Methods (407 papers) and Advanced Image and Video Retrieval Techniques (391 papers). The most active scholars publishing in Machine Vision and Applications are Thomas B. Moeslund, Pascal Fua, Paul L. Rosin, Paul J. Besl, Mubarak Shah, Rikke Gade, Kamal Nasrollahi, Olivier Faugeras, Frédéric Devernay and K. Krishna Reddy.

In The Last Decade

Fields of papers published in Machine Vision and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Machine Vision and Applications. 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 Machine Vision and Applications.

Countries where authors publish in Machine Vision and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Machine Vision and Applications. 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 Machine Vision and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Machine Vision and Applications 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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2025