International Journal of Machine Learning and Cybernetics

2.3k papers and 30.3k indexed citations i.

About

The 2.3k papers published in International Journal of Machine Learning and Cybernetics in the last decades have received a total of 30.3k indexed citations. Papers published in International Journal of Machine Learning and Cybernetics usually cover Artificial Intelligence (1.2k papers), Computer Vision and Pattern Recognition (793 papers) and Computational Theory and Mathematics (431 papers) specifically the topics of Rough Sets and Fuzzy Logic (320 papers), Face and Expression Recognition (282 papers) and Multi-Criteria Decision Making (203 papers). The most active scholars publishing in International Journal of Machine Learning and Cybernetics are Guang-Bin Huang, Yuan Lan, Yiyu Yao, Ali Wagdy Mohamed, Zhi-Hua Zhou, Rong Jin, Yin Zhang, Ali Khater Mohamed, İrfan Deli̇ and Xizhao Wang.

In The Last Decade

Fields of papers published in International Journal of Machine Learning and Cybernetics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in International Journal of Machine Learning and Cybernetics. 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 International Journal of Machine Learning and Cybernetics.

Countries where authors publish in International Journal of Machine Learning and Cybernetics

Since Specialization
Citations

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