Chaochen Gu

993 citations
74 papers · 704 · h-index 14

Impact in

Papers in

Chaochen Gu

69 papers receiving 685 citations

Peers

Chaochen Gu
Comparison fields: 5 of 102
  • Computer Vision and Pattern Recognition 280
  • Media Technology 68
  • Artificial Intelligence 174
  • Industrial and Manufacturing Engineering 44
  • Biophysics 22
Replace Liu Li with:
Liu Li China
Jungsuk Kim South Korea
Xinrong Hu China
Xuenan Cui South Korea
Kaijie Wu China
Kenichi Ohara Japan
Jiakun Li China
Zhiqin Qian China
Yiren Zhou China
Chaochen Gu relative to Liu Li China Liu Li's profile →
Citations per field
00.5×2×3.2×
Liu Li · 1×
Citations per year

Countries citing papers authored by Chaochen Gu

Since Specialization
Citations

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

Fields of papers citing papers by Chaochen Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021120
2 200945
3 200244
4 201137
5 202235
6 202332
7 201822
8 202320
9 200819
10 201718
11 202018
12 200817
13 202017
14 201516
15 201514
16 202413
17 202112
18 201512
19 201611
20 202210

About Chaochen Gu

Chaochen Gu is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Industrial and Manufacturing Engineering and Control and Systems Engineering, having authored 74 papers that have together received 704 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Shape Memory Alloy Transformations (6 papers), AI in cancer detection (6 papers), Advanced Image and Video Retrieval Techniques (6 papers), Robot Manipulation and Learning (5 papers), Image Processing Techniques and Applications (5 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (280 citations), Media Technology (68 citations), Artificial Intelligence (174 citations), Industrial and Manufacturing Engineering (44 citations) and Biophysics (22 citations). Chaochen Gu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Kaijie Wu, Kai Yang, Xinping Guan, Yuchao Dai, Fei Zhang, Jie Hu, Yinghong Peng, Changsheng Lu, Sheng Li and Shanying Zhu. Their work appears in journals such as Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science, Multimedia Tools and Applications, Applied Sciences, IEEE Transactions on Industrial Informatics and IEEE Transactions on Consumer Electronics.

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.

Explore authors with similar magnitude of impact