Shen Ge

About

Shen Ge is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Shen Ge has authored 24 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Networks and Communications. Recurrent topics in Shen Ge’s work include Multimodal Machine Learning Applications (9 papers), Topic Modeling (9 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Shen Ge is often cited by papers focused on Multimodal Machine Learning Applications (9 papers), Topic Modeling (9 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Shen Ge collaborates with scholars based in China, Hong Kong and United States. Shen Ge's co-authors include Xian Wu, Fenglin Liu, Yuexian Zou, Wei Fan, Nikos Mamoulis, Panagiotis Bouros, Yan Qiao, Bin Yu, Li Xiao and Xu Sun and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering and Medical Image Analysis.

In The Last Decade

Co-authorship network of co-authors of Shen Ge i

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Fields of papers citing papers by Shen Ge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Shen Ge

Since Specialization

Citations

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