Guanhang Wu

1.4k total citations
7 papers, 395 citations indexed

About

Guanhang Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Guanhang Wu has authored 7 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Guanhang Wu's work include Multimodal Machine Learning Applications (3 papers), Human Pose and Action Recognition (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Guanhang Wu is often cited by papers focused on Multimodal Machine Learning Applications (3 papers), Human Pose and Action Recognition (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Guanhang Wu collaborates with scholars based in United States, Portugal and Mexico. Guanhang Wu's co-authors include José M. F. Moura, Geoffrey J. Gordon, João Paulo Costeira, Shanghang Zhang, Han Zhao, Roberta L. Klatzky, Brandon Amos, Mahadev Satyanarayanan, Zhuo Chen and Daniel P. Siewiorek and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Guanhang Wu

7 papers receiving 382 citations

Peers

Guanhang Wu
Comparison fields: 5 of 72
  • Artificial Intelligence 192
  • Computer Vision and Pattern Recognition 186
  • Computer Networks and Communications 127
  • Information Systems 45
  • Electrical and Electronic Engineering 41
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Citations per field, relative to Guanhang Wu
Guanhang Wu · 1×
Citations per year, relative to Guanhang Wu
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Countries citing papers authored by Guanhang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Guanhang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guanhang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Guanhang Wu. A scholar is included among the top collaborators of Guanhang 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 Guanhang Wu. Guanhang Wu 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
# Work Indexed citations
1 4
2 5
3 25
4
Long Term Temporal Context for Per-Camera Object Detection
2
5
Multiple Source Domain Adaptation with Adversarial Learning
30
6
Adversarial Multiple Source Domain Adaptation
176
7 153

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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