Guan Huang

146 total papers · 4.6k total citations
77 papers, 2.3k citations indexed

About

Guan Huang is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Materials Chemistry. According to data from OpenAlex, Guan Huang has authored 77 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 11 papers in Biomedical Engineering and 7 papers in Materials Chemistry. Recurrent topics in Guan Huang's work include Advanced Neural Network Applications (11 papers), Video Surveillance and Tracking Methods (9 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Guan Huang is often cited by papers focused on Advanced Neural Network Applications (11 papers), Video Surveillance and Tracking Methods (9 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Guan Huang collaborates with scholars based in China, United States and Australia. Guan Huang's co-authors include Zheng Zhu, Ronald Klein, James S. Pankow, Jiwen Lu, Jie Zhou, Dalong Du, Karen J. Cruickshanks, Xingang Wang, Xinze Chen and Yongming Rao and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Guan Huang

68 papers receiving 2.2k citations

Hit Papers

DenseCLIP: Language-Guide... 2022 2026 2023 2024 2022 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Guan Huang 1.1k 450 414 245 236 77 2.3k
Kevin McGuinness 1.0k 1.0× 553 1.2× 95 0.2× 106 0.4× 122 0.5× 124 2.6k
Min Fu 227 0.2× 246 0.5× 88 0.2× 67 0.3× 91 0.4× 116 1.8k
Qi Li 473 0.4× 234 0.5× 133 0.3× 89 0.4× 513 2.2× 161 1.7k
Ming Yang 389 0.4× 409 0.9× 257 0.6× 157 0.6× 680 2.9× 67 2.1k
Paul Green 159 0.2× 188 0.4× 102 0.2× 96 0.4× 292 1.2× 162 3.3k
Armando Barreto 476 0.4× 219 0.5× 15 0.0× 451 1.8× 936 4.0× 185 3.1k
Tam Nguyen 1.3k 1.2× 359 0.8× 104 0.3× 81 0.3× 84 0.4× 140 1.9k
Stephanie Schuckers 1.1k 1.0× 158 0.4× 18 0.0× 398 1.6× 228 1.0× 165 3.2k
Arindam Dey 962 0.9× 84 0.2× 35 0.1× 36 0.1× 309 1.3× 98 1.9k
Alessandro Micarelli 159 0.2× 410 0.9× 217 0.5× 77 0.3× 148 0.6× 147 1.9k

Countries citing papers authored by Guan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Guan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guan Huang

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