Song Tang

39 papers and 397 indexed citations i.

About

Song Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Song Tang has authored 39 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Song Tang’s work include Domain Adaptation and Few-Shot Learning (14 papers), Multimodal Machine Learning Applications (11 papers) and Advanced Neural Network Applications (7 papers). Song Tang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (14 papers), Multimodal Machine Learning Applications (11 papers) and Advanced Neural Network Applications (7 papers). Song Tang collaborates with scholars based in China, Germany and United Kingdom. Song Tang's co-authors include Jianwei Zhang, Hongzhuo Liang, Shuang Li, Fuchun Sun, Michael Görner, Bin Fang, Xiaojian Ma, Mao Ye, Xudong Li and Yiguang Liu and has published in prestigious journals such as Environment International, Expert Systems with Applications and IEEE Access.

In The Last Decade

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

Fields of papers citing papers by Song Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Song Tang

Since Specialization
Citations

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