Min Fang

43 papers and 387 indexed citations i.

About

Min Fang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Min Fang has authored 43 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Min Fang’s work include Domain Adaptation and Few-Shot Learning (20 papers), Machine Learning and ELM (7 papers) and Text and Document Classification Technologies (7 papers). Min Fang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (20 papers), Machine Learning and ELM (7 papers) and Text and Document Classification Technologies (7 papers). Min Fang collaborates with scholars based in China and The Netherlands. Min Fang's co-authors include Xiao Li, Xiao Li, Yong Guo, Xiaosong Zhang, Xiao Li, Li Xiao, Da‐Zheng Feng, Nian Wang, Hongchun Wang and Xiao Li and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Co-authorship network of co-authors of Min Fang i

Fields of papers citing papers by Min Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min Fang. 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 Fang. The network helps show where Min Fang may publish in the future.

Countries citing papers authored by Min Fang

Since Specialization
Citations

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