Journal of Mathematical Imaging and Vision

1.5k papers and 31.8k indexed citations i.

About

The 1.5k papers published in Journal of Mathematical Imaging and Vision in the last decades have received a total of 31.8k indexed citations. Papers published in Journal of Mathematical Imaging and Vision usually cover Computer Vision and Pattern Recognition (1.2k papers), Computational Mechanics (368 papers) and Media Technology (199 papers) specifically the topics of Medical Image Segmentation Techniques (495 papers), Image and Signal Denoising Methods (302 papers) and Advanced Vision and Imaging (265 papers). The most active scholars publishing in Journal of Mathematical Imaging and Vision are Mila Nikolova, Thomas Pock, Antonin Chambolle, Xavier Pennec, Tony Lindeberg, Du Q. Huynh, Laurence Boxer, Alfred O. Hero, Jia Li and Joachim Weickert.

In The Last Decade

Fields of papers published in Journal of Mathematical Imaging and Vision

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of Mathematical Imaging and Vision. 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 Journal of Mathematical Imaging and Vision.

Countries where authors publish in Journal of Mathematical Imaging and Vision

Since Specialization
Citations

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