Qing Guo

244 total papers · 5.5k total citations
118 papers, 2.3k citations indexed

About

Qing Guo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Qing Guo has authored 118 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Computer Vision and Pattern Recognition, 45 papers in Artificial Intelligence and 12 papers in Computer Networks and Communications. Recurrent topics in Qing Guo's work include Adversarial Robustness in Machine Learning (27 papers), Video Surveillance and Tracking Methods (16 papers) and Image Enhancement Techniques (13 papers). Qing Guo is often cited by papers focused on Adversarial Robustness in Machine Learning (27 papers), Video Surveillance and Tracking Methods (16 papers) and Image Enhancement Techniques (13 papers). Qing Guo collaborates with scholars based in China, Singapore and United States. Qing Guo's co-authors include Wei Feng, Song Wang, Felix Juefei-Xu, Yang Liu, Liang Wan, Ce Zhou, Rui Huang, Lei Ma, Xiaofei Xie and Yihao Huang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Qing Guo

104 papers receiving 2.2k citations

Hit Papers

Learning Dynamic Siamese ... 2017 2026 2020 2023 2017 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Qing Guo 1.7k 569 298 237 187 118 2.3k
Qiang Wang 1.6k 0.9× 328 0.6× 335 1.1× 199 0.8× 215 1.1× 159 2.2k
Ming Tang 1.7k 1.0× 547 1.0× 260 0.9× 151 0.6× 215 1.1× 109 2.3k
James Ferryman 1.8k 1.1× 658 1.2× 213 0.7× 108 0.5× 106 0.6× 112 2.3k
Liang Wan 1.8k 1.0× 228 0.4× 276 0.9× 209 0.9× 264 1.4× 111 2.2k
Zhenyu He 2.4k 1.4× 579 1.0× 709 2.4× 420 1.8× 192 1.0× 99 3.2k
Kai‐Lung Hua 1.2k 0.7× 480 0.8× 150 0.5× 98 0.4× 262 1.4× 141 2.3k
Qiang Wang 2.5k 1.5× 445 0.8× 729 2.4× 552 2.3× 225 1.2× 79 3.0k
Wei Feng 2.5k 1.5× 408 0.7× 475 1.6× 260 1.1× 394 2.1× 133 3.0k
Yuankai Qi 1.6k 0.9× 557 1.0× 310 1.0× 224 0.9× 77 0.4× 64 1.9k
Xiangyuan Lan 2.8k 1.6× 388 0.7× 402 1.3× 175 0.7× 222 1.2× 61 3.3k

Countries citing papers authored by Qing Guo

Since Specialization
Citations

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

Fields of papers citing papers by Qing Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Guo. A scholar is included among the top collaborators of Qing 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 Qing Guo. Qing 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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