Cun Mu

About

Cun Mu is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Biomedical Engineering. According to data from OpenAlex, Cun Mu has authored 7 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Computational Mechanics and 2 papers in Biomedical Engineering. Recurrent topics in Cun Mu’s work include Sparse and Compressive Sensing Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Tensor decomposition and applications (2 papers). Cun Mu is often cited by papers focused on Sparse and Compressive Sensing Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Tensor decomposition and applications (2 papers). Cun Mu collaborates with scholars based in United States, Hong Kong and China. Cun Mu's co-authors include Shih‐Fu Chang, Wei Liu, Sanjiv Kumar, Donald Goldfarb, John Wright, Yuqian Zhang, Daniel Hsu, Shiqian Ma, Rongrong Ji and John Smith and has published in prestigious journals such as SIAM Journal on Scientific Computing, SIAM Journal on Matrix Analysis and Applications and Computational Optimization and Applications.

In The Last Decade

Co-authorship network of co-authors of Cun Mu i

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Fields of papers citing papers by Cun Mu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Cun Mu

Since Specialization

Citations

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