Min-Chul Yang

About

Min-Chul Yang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Min-Chul Yang has authored 8 papers receiving a total of 166 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Min-Chul Yang’s work include Topic Modeling (4 papers), Multimodal Machine Learning Applications (2 papers) and Complex Network Analysis Techniques (2 papers). Min-Chul Yang is often cited by papers focused on Topic Modeling (4 papers), Multimodal Machine Learning Applications (2 papers) and Complex Network Analysis Techniques (2 papers). Min-Chul Yang collaborates with scholars based in South Korea, United States and China. Min-Chul Yang's co-authors include Hae‐Chang Rim, Jung‐Tae Lee, Ming Zhou, Nan Duan, Chanyoung Park, Soyoung Park, Seung-Wook Lee, Hwanjo Yu, S. K. Choi and Hwanjo Yu and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and CiteSeer X (The Pennsylvania State University).

In The Last Decade

Co-authorship network of co-authors of Min-Chul Yang i

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Fields of papers citing papers by Min-Chul Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min-Chul Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Min-Chul Yang. The network helps show where Min-Chul Yang may publish in the future.

Countries citing papers authored by Min-Chul Yang

Since Specialization

Citations

This map shows the geographic impact of Min-Chul Yang's research. 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 Min-Chul Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min-Chul Yang 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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