Tsz-Ho Yu
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 2%
- Control and Systems Engineering top 10%
- Artificial Intelligence
- Biomedical Engineering
- Co-authors
- Tae‐Kyun KimRoberto CipollaDanhang TangOliver J. WoodfordChengde WanChristopher D. TwiggGang DongYuting Ye
- Topics
- Human Pose and Action Recognition (4 papers)Hand Gesture Recognition Systems (3 papers)Advanced Image and Video Retrieval Techniques (2 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- ACM Transactions on GraphicsInternational Journal of Computer VisionMachine Vision and Applications
- Partner nations
- United KingdomIsraelJapan
In The Last Decade
Tsz-Ho Yu
7 papers receiving 415 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 336
- Human-Computer Interaction 225
- Control and Systems Engineering 110
- Artificial Intelligence 58
- Biomedical Engineering 43
Countries citing papers authored by Tsz-Ho Yu
This map shows the geographic impact of Tsz-Ho Yu'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 Tsz-Ho Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tsz-Ho Yu more than expected).
Fields of papers citing papers by Tsz-Ho Yu
This network shows the impact of papers produced by Tsz-Ho Yu. 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 Tsz-Ho Yu. The network helps show where Tsz-Ho Yu may publish in the future.
Co-authorship network of co-authors of Tsz-Ho Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Tsz-Ho Yu. A scholar is included among the top collaborators of Tsz-Ho Yu 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 Tsz-Ho Yu. Tsz-Ho Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 132 | |
| 2 | 126 | |
| 3 | 35 | |
| 4 | 28 | |
| 5 | 7 | |
| 6 | 89 | |
| 7 | An Intelligent Night Vision System for Automobiles | 8 |
About Tsz-Ho Yu
Tsz-Ho Yu is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Geography, Planning and Development, having authored 7 papers that have together received 425 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Hand Gesture Recognition Systems (3 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Human-Computer Interaction (225 citations), Computer Vision and Pattern Recognition (336 citations) and Control and Systems Engineering (110 citations). Tsz-Ho Yu has collaborated with scholars based in United Kingdom, Israel and Japan. Frequent co-authors include Tae‐Kyun Kim, Roberto Cipolla, Danhang Tang, Oliver J. Woodford, Chengde Wan, Christopher D. Twigg, Gang Dong, Yuting Ye, Lingling Tao and Peizhao Zhang. Their work appears in journals such as ACM Transactions on Graphics, International Journal of Computer Vision and Machine Vision and Applications.
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.