Frontiers in Computer Science

579 papers and 3.4k indexed citations i.

About

The 579 papers published in Frontiers in Computer Science in the last decades have received a total of 3.4k indexed citations. Papers published in Frontiers in Computer Science usually cover Artificial Intelligence (161 papers), Computer Vision and Pattern Recognition (102 papers) and Human-Computer Interaction (88 papers) specifically the topics of Virtual Reality Applications and Impacts (36 papers), Innovative Human-Technology Interaction (34 papers) and Emotion and Mood Recognition (30 papers). The most active scholars publishing in Frontiers in Computer Science are Jasmine Paul, Felicia Jefferson, Won‐Ki Jeong, Tran Minh Quan, David G. C. Hildebrand, Liqaa Nawaf, Imtiaz Khan, Chaminda Hewage, Foivos Psarommatis and Gökan May.

In The Last Decade

Fields of papers published in Frontiers in Computer Science

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Frontiers in Computer Science. 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 Frontiers in Computer Science.

Countries where authors publish in Frontiers in Computer Science

Since Specialization
Citations

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