Long Chen

137 papers and 4.1k indexed citations i.

About

Long Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Long Chen has authored 137 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 57 papers in Computer Vision and Pattern Recognition and 20 papers in Information Systems. Recurrent topics in Long Chen’s work include Multimodal Machine Learning Applications (37 papers), Domain Adaptation and Few-Shot Learning (26 papers) and Topic Modeling (21 papers). Long Chen is often cited by papers focused on Multimodal Machine Learning Applications (37 papers), Domain Adaptation and Few-Shot Learning (26 papers) and Topic Modeling (21 papers). Long Chen collaborates with scholars based in China, United States and Hong Kong. Long Chen's co-authors include Jun Xiao, Hanwang Zhang, Wei Liu, Jian Shao, Tat‐Seng Chua, Liqiang Nie, Robert S. Goldstein, Pierre Collin‐Dufresne, Xinlei Zhao and Shih‐Fu Chang and has published in prestigious journals such as Physical Review B, IEEE Transactions on Pattern Analysis and Machine Intelligence and Water Research.

In The Last Decade

Co-authorship network of co-authors of Long Chen i

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Fields of papers citing papers by Long Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Long Chen

Since Specialization

Citations

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