Kai‐Tai Song

About

Kai‐Tai Song is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Control and Systems Engineering. According to data from OpenAlex, Kai‐Tai Song has authored 74 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Vision and Pattern Recognition, 29 papers in Aerospace Engineering and 21 papers in Control and Systems Engineering. Recurrent topics in Kai‐Tai Song’s work include Robotics and Sensor-Based Localization (29 papers), Robotic Path Planning Algorithms (21 papers) and Advanced Vision and Imaging (15 papers). Kai‐Tai Song is often cited by papers focused on Robotics and Sensor-Based Localization (29 papers), Robotic Path Planning Algorithms (21 papers) and Advanced Vision and Imaging (15 papers). Kai‐Tai Song collaborates with scholars based in Taiwan, Belgium and United States. Kai‐Tai Song's co-authors include Ching‐Cheng Teng, Ti-Chung Lee, Ching‐Hung Lee, Chi‐Yi Tsai, Ching‐Po Lin, Chun-Chieh Chen, Hendrik Van Brussel, Marnix Nuttin, Yiwen Chen and Jen‐Hao Chen and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Industrial Electronics and IEEE Transactions on Image Processing.

In The Last Decade

Co-authorship network of co-authors of Kai‐Tai Song i

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Fields of papers citing papers by Kai‐Tai Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Kai‐Tai Song

Since Specialization

Citations

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