Gu Fang

3.6k citations
178 papers · 2.7k · 1 hit paper · h-index 26

Impact in

Papers in

Gu Fang

163 papers receiving 2.6k citations

Gu Fang's Hit Papers

Human Object Recognition Using Colour and Depth Information from an RGB-D Kinect Sensor 2013 · 300 citations
3000+4+8Years since publication100200300

Peers

Gu Fang
Comparison fields: 5 of 163
  • Computer Vision and Pattern Recognition 849
  • Industrial and Manufacturing Engineering 327
  • Biological Psychiatry 66
  • Media Technology 167
  • Mechanical Engineering 663
Replace Ying He with:
Ying He China
Song Chen China
J. Michael McCarthy United States
Kaixin Wang China
Yongsheng Zhu China
Chi Zhang China
Zhibo Chen China
Carlos Marques Portugal
Hongmin Liu China
Gu Fang relative to Ying He China Ying He's profile →
Citations per field
00.5×2.9×
Ying He · 1×
Citations per year

Countries citing papers authored by Gu Fang

Since Specialization
Citations

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

Fields of papers citing papers by Gu Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gu Fang, 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 Gu Fang Line = papers co-authored together Gu Fang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 178 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Human Object Recognition Using Colour and Depth Information from an RGB-D Kinect Sensor
Hit paper breakdown →
2013300
2 2013124
3 2013112
4 2014111
5 2004101
6 201493
7 202091
8 200584
9 201075
10 201772
11 200663
12 200861
13 201260
14 201754
15 201352
16 201350
17 201243
18 201936
19 201335
20 201333

About Gu Fang

Gu Fang is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering and Atomic and Molecular Physics, and Optics, having authored 178 papers that have together received 2.7k indexed citations. Recurring topics across this work include Image Enhancement Techniques (26 papers), Welding Techniques and Residual Stresses (15 papers), Video Surveillance and Tracking Methods (12 papers), Phase Equilibria and Thermodynamics (11 papers), Advanced Image Fusion Techniques (11 papers), Advanced Vision and Imaging (10 papers), Robotics and Sensor-Based Localization (10 papers) and Color Science and Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (849 citations), Industrial and Manufacturing Engineering (327 citations), Biological Psychiatry (66 citations), Media Technology (167 citations) and Mechanical Engineering (663 citations). Gu Fang has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Benjamin J. Southwell, N. M. Kwok, Ju Jia Zou, Q. P. Ha, Shanben Chen, Yanling Xu, Zhen Ye, Na Lv, C.J. Liu and Ataur Rahman. Their work appears in journals such as Optik, Optics Communications, The International Journal of Advanced Manufacturing Technology, Robotics and Computer-Integrated Manufacturing and Chinese Physics Letters.

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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