Jun Guo

1.6k citations
61 papers · 1.0k · h-index 20

Impact in

Papers in

Jun Guo

58 papers receiving 1.0k citations

Peers

Jun Guo
Comparison fields: 5 of 112
  • Computer Vision and Pattern Recognition 552
  • Media Technology 124
  • Artificial Intelligence 382
  • Computational Mathematics 6
  • Urban Studies 35
Replace Xiaohong Zhang with:
Xiaohong Zhang China
Andreas Veit United States
Jingbin Wang China
Martin Silbiger United States
Keng Yeow Tay Canada
Xiaoshuang Shi China
Zengchang Qin China
Kerstin Bunte Netherlands
Arnold Wiliem Australia
Yunfan Li China
Jun Guo relative to Xiaohong Zhang China Xiaohong Zhang's profile →
Citations per field
00.5×1.5×2.3×
Xiaohong Zhang · 1×
Citations per year

Countries citing papers authored by Jun Guo

Since Specialization
Citations

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

Fields of papers citing papers by Jun Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Guo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Guo Line = papers co-authored together Jun Guo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201992
2 201880
3 201569
4 201763
5 201957
6 202155
7 201651
8 202046
9 202139
10 200838
11 201931
12 201529
13 201928
14 201526
15 201725
16 201824
17 201523
18 201822
19 201520
20 201719

About Jun Guo

Jun Guo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Signal Processing and Computational Mechanics, having authored 61 papers that have together received 1.0k indexed citations. Recurring topics across this work include Face and Expression Recognition (19 papers), Advanced Image and Video Retrieval Techniques (14 papers), Advanced Algorithms and Applications (7 papers), Domain Adaptation and Few-Shot Learning (6 papers), Blind Source Separation Techniques (5 papers), Advanced Vision and Imaging (5 papers), Sparse and Compressive Sensing Techniques (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (552 citations), Media Technology (124 citations), Artificial Intelligence (382 citations), Computational Mathematics (6 citations) and Urban Studies (35 citations). Jun Guo has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Wenwu Zhu, Jiahui Ye, Xiangwei Kong, Yanqing Guo, Ran He, Hongyang Chao, Norikazu Takahashi, Tetsuo Nishi, Changhu Wang and Edgar Román-Rangel. Their work appears in journals such as Neurocomputing, IEEE Transactions on Image Processing, Ocean Engineering, Frontiers in Oncology and Epidemiology and Infection.

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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