Cong Yang

683 citations
38 papers · 431 · h-index 13

Impact in

Papers in

Cong Yang

35 papers receiving 410 citations

Peers

Cong Yang
Comparison fields: 5 of 83
  • Computer Vision and Pattern Recognition 227
  • Human-Computer Interaction 38
  • Space and Planetary Science 5
  • Catalysis 22
  • Artificial Intelligence 94
Replace Takuya Akashi with:
Takuya Akashi Japan
Shenglin Mu Japan
Zhiwei Zhong China
Junho Kim South Korea
Hong Qiao China
Shaopeng Guo China
A F M Saifuddin Saif Bangladesh
Shijie Cai China
Jiandan Zhong China
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Citations per field
00.5×1.5×2.2×
Takuya Akashi · 1×
Citations per year

Countries citing papers authored by Cong Yang

Since Specialization
Citations

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

Fields of papers citing papers by Cong Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200970
2 200844
3 201242
4 202434
5 197233
6 201626
7 201016
8 201016
9 201014
10 202213
11 202013
12 202312
13 201012
14 197211
15 19908
16 20247
17 20197
18 20236
19 20245
20 20225

About Cong Yang

Cong Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Environmental Engineering and Molecular Biology, having authored 38 papers that have together received 431 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (10 papers), Video Surveillance and Tracking Methods (7 papers), Robotics and Sensor-Based Localization (5 papers), Image Processing and 3D Reconstruction (4 papers), Remote Sensing and LiDAR Applications (4 papers), Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (3 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (227 citations), Human-Computer Interaction (38 citations), Space and Planetary Science (5 citations), Catalysis (22 citations) and Artificial Intelligence (94 citations). Cong Yang has collaborated with scholars based in China, Germany and Malaysia. Frequent co-authors include Yandong Tang, Haifeng Gong, Song‐Chun Zhu, M.B. Cutlip, C.O. Bennett, Marcin Grzegorzek, Zuchao Li, Lefei Zhang, John See and Xiaomao Li. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Automation Science and Engineering, BMC Systems Biology and IEEE Transactions on Intelligent Transportation Systems.

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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