Kai Guo

44 total papers · 539 total citations
28 papers, 327 citations indexed

About

Kai Guo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Kai Guo has authored 28 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 6 papers in Media Technology. Recurrent topics in Kai Guo's work include Advanced Image Processing Techniques (7 papers), Image and Signal Denoising Methods (7 papers) and Anomaly Detection Techniques and Applications (7 papers). Kai Guo is often cited by papers focused on Advanced Image Processing Techniques (7 papers), Image and Signal Denoising Methods (7 papers) and Anomaly Detection Techniques and Applications (7 papers). Kai Guo collaborates with scholars based in China, United States and South Korea. Kai Guo's co-authors include Janusz Konrad, Prakash Ishwar, Weiyao Lin, Songyu Yu, Hongyuan Zha, Xiaokang Yang, Xiaokang Yang, R. Zhang, Xiyuan Peng and Datong Liu and has published in prestigious journals such as IEEE Transactions on Image Processing, Remote Sensing and Mechanics of Materials.

In The Last Decade

Kai Guo

23 papers receiving 312 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kai Guo 276 88 86 43 35 28 327
Chengcheng Jia 179 0.6× 58 0.7× 95 1.1× 17 0.4× 35 1.0× 24 308
Wanjun Chen 189 0.7× 54 0.6× 119 1.4× 47 1.1× 24 0.7× 22 306
Haitian Zheng 194 0.7× 41 0.5× 64 0.7× 67 1.6× 22 0.6× 24 322
Stephan Liwicki 265 1.0× 44 0.5× 57 0.7× 33 0.8× 111 3.2× 18 359
Shagan Sah 150 0.5× 26 0.3× 110 1.3× 17 0.4× 42 1.2× 23 333
Yuanrong Xu 240 0.9× 27 0.3× 96 1.1× 61 1.4× 31 0.9× 24 361
Kwon Junghyun 273 1.0× 24 0.3× 72 0.8× 30 0.7× 22 0.6× 23 365
Xiaodong Yu 261 0.9× 59 0.7× 62 0.7× 25 0.6× 14 0.4× 28 312
Hanling Zhang 258 0.9× 45 0.5× 55 0.6× 17 0.4× 40 1.1× 35 324
Kha Gia Quach 290 1.1× 17 0.2× 52 0.6× 59 1.4× 45 1.3× 19 353

Countries citing papers authored by Kai Guo

Since Specialization
Citations

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

Fields of papers citing papers by Kai Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Guo. A scholar is included among the top collaborators of Kai Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kai Guo. Kai Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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