Image and Vision Computing

3.9k papers and 101.9k indexed citations i.

About

The 3.9k papers published in Image and Vision Computing in the last decades have received a total of 101.9k indexed citations. Papers published in Image and Vision Computing usually cover Computer Vision and Pattern Recognition (3.4k papers), Artificial Intelligence (572 papers) and Aerospace Engineering (547 papers) specifically the topics of Advanced Vision and Imaging (811 papers), Advanced Image and Video Retrieval Techniques (719 papers) and Medical Image Segmentation Techniques (521 papers). The most active scholars publishing in Image and Vision Computing are Barbara Zitová, Jan Flusser, Ronald Poppe, Gérard Medioni, Yang Chen, Jiřı́ Matas, Maja Pantić, Zhengyou Zhang, Ondřej Chum and Shaogang Gong.

In The Last Decade

Fields of papers published in Image and Vision Computing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Image and Vision Computing. 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 Image and Vision Computing.

Countries where authors publish in Image and Vision Computing

Since Specialization
Citations

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