Zilin Gao

883 citations
7 papers · 542 indexed · 1 hit paper · h-index 5
Topics
Human Pose and Action Recognition (3 papers)Advanced Neural Network Applications (3 papers)Domain Adaptation and Few-Shot Learning (2 papers)

In The Last Decade

Zilin Gao

5 papers receiving 533 citations

Hit Papers

Global Second-Order Pooling Convolutional Networks20192026202120232019100200300

Peers

Zilin Gao
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 407
  • Artificial Intelligence 195
  • Media Technology 92
  • Radiology, Nuclear Medicine and Imaging 49
  • Aerospace Engineering 37
Replace Feifei Lee with:
Feifei Lee Japan
Yunhang Shen China
Linfeng Xu China
Zhongying Deng China
Zongxin Yang China
Dilin Wang United States
Sucheng Ren China
Guoheng Huang China
Zilin Gao relative to Feifei Lee Japan Feifei Lee's profile →
Citations per field
00.5×1.6×
Feifei Lee · 1×
Citations per year

Countries citing papers authored by Zilin Gao

Since Specialization
Citations

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

Fields of papers citing papers by Zilin Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zilin Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Zilin Gao. A scholar is included among the top collaborators of Zilin Gao 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 Zilin Gao. Zilin Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 0
2 0
3 10
4 5
5
Global Second-Order Pooling Convolutional Networksbreakdown →
324
6
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
7
7 196

About Zilin Gao

Zilin Gao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Rehabilitation, having authored 7 papers that have together received 542 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (3 papers), Advanced Neural Network Applications (3 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (407 citations), Media Technology (92 citations) and Artificial Intelligence (195 citations). Zilin Gao has collaborated with scholars based in China, Nigeria and Cayman Islands. Frequent co-authors include Peihua Li, Qilong Wang, Jiangtao Xie, Qinghua Hu, Wangmeng Zuo, Yuming Feng, Xiaofeng Liao, Qinghua Hu, Zhaofeng Chen and Shan Jiang. Their work appears in journals such as PLoS ONE, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.

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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