Shao-Bo Lin

About

Shao-Bo Lin is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shao-Bo Lin has authored 60 papers receiving a total of 979 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 27 papers in Computational Mechanics and 25 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shao-Bo Lin’s work include Neural Networks and Applications (23 papers), Sparse and Compressive Sensing Techniques (23 papers) and Machine Learning and ELM (14 papers). Shao-Bo Lin is often cited by papers focused on Neural Networks and Applications (23 papers), Sparse and Compressive Sensing Techniques (23 papers) and Machine Learning and ELM (14 papers). Shao-Bo Lin collaborates with scholars based in China, Hong Kong and United States. Shao-Bo Lin's co-authors include Ding‐Xuan Zhou, Zongben Xu, Jian Fang, Jinshan Zeng, Zheng-Chu Guo, Zongben Xu, Xia Liu, Xiangyu Chang, Yao Wang and Feilong Cao and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Theory and IEEE Transactions on Signal Processing.

In The Last Decade

Co-authorship network of co-authors of Shao-Bo Lin i

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Fields of papers citing papers by Shao-Bo Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao-Bo Lin. 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 Shao-Bo Lin. The network helps show where Shao-Bo Lin may publish in the future.

Countries citing papers authored by Shao-Bo Lin

Since Specialization

Citations

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