Songlin Dong

About

Songlin Dong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Songlin Dong has authored 15 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Songlin Dong’s work include Domain Adaptation and Few-Shot Learning (12 papers), Multimodal Machine Learning Applications (9 papers) and Machine Learning and ELM (7 papers). Songlin Dong is often cited by papers focused on Domain Adaptation and Few-Shot Learning (12 papers), Multimodal Machine Learning Applications (9 papers) and Machine Learning and ELM (7 papers). Songlin Dong collaborates with scholars based in China, Poland and Singapore. Songlin Dong's co-authors include Yihong Gong, Xiaoyu Tao, Xiaopeng Hong, Xing Wei, Xinyuan Chang, Jingang Shi, Yu Liu, Zitong Yu, Shaokun Wang and Cynthia Wang and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Co-authorship network of co-authors of Songlin Dong i

Layout:

Gravity: 0.05 Iterations: 100 Initial Temp: 1000 Cooling: 0.99 Min Temp: 1

Fields of papers citing papers by Songlin Dong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Songlin Dong

Since Specialization

Citations

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

Explore authors with similar magnitude of impact