Mingqian Tang

About

Mingqian Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Mingqian Tang has authored 6 papers receiving a total of 107 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Biomedical Engineering. Recurrent topics in Mingqian Tang’s work include Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Mingqian Tang is often cited by papers focused on Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Mingqian Tang collaborates with scholars based in China, Singapore and United States. Mingqian Tang's co-authors include Nong Sang, Zhiwu Qing, Xiang Wang, Changxin Gao, Rong Jin, Shiwei Zhang, Wei Tong, Jianwen Jiang, Yu-Feng Li and Shiwei Zhang and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Co-authorship network of co-authors of Mingqian Tang i

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Fields of papers citing papers by Mingqian Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Mingqian Tang

Since Specialization

Citations

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