Xinxiao Wu

1.8k total citations
71 papers, 1.1k citations indexed

About

Xinxiao Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Xinxiao Wu has authored 71 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Vision and Pattern Recognition, 32 papers in Artificial Intelligence and 13 papers in Biomedical Engineering. Recurrent topics in Xinxiao Wu's work include Human Pose and Action Recognition (48 papers), Multimodal Machine Learning Applications (41 papers) and Domain Adaptation and Few-Shot Learning (16 papers). Xinxiao Wu is often cited by papers focused on Human Pose and Action Recognition (48 papers), Multimodal Machine Learning Applications (41 papers) and Domain Adaptation and Few-Shot Learning (16 papers). Xinxiao Wu collaborates with scholars based in China, United States and Singapore. Xinxiao Wu's co-authors include Yunde Jia, Jiebo Luo, Lixin Duan, Wentian Zhao, Dong Xu, Xiaoxun Zhang, Wei Liang, Cuiwei Liu, Mei Chen and Yuchao Sun and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Xinxiao Wu

68 papers receiving 1.1k citations

Peers

Xinxiao Wu
Comparison fields: 5 of 74
  • Computer Vision and Pattern Recognition 966
  • Artificial Intelligence 560
  • Biomedical Engineering 195
  • Human-Computer Interaction 112
  • Computer Networks and Communications 71
Replace Pradeep Natarajan with:
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Pradeep Natarajan United States View profile →
Citations per field, relative to Xinxiao Wu
Xinxiao Wu · 1×
Citations per year, relative to Xinxiao Wu
Xinxiao Wu · 1×

Countries citing papers authored by Xinxiao Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xinxiao Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinxiao Wu

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 6
2 1
3 2
4 0
5 0
6 11
7 3
8
Multi-modal Dependency Tree for Video Captioning
11
9 11
10 46
11 1
12 63
13 13
14 4
15 8
16 10
17 165
18 17
19 2
20
Hand Motion Tracking Using Simulated Annealing Method in a Discrete Space
1

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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