Yuan-Ting Hu
- Computer Vision and Pattern Recognition top 10%
- Aerospace Engineering
- Artificial Intelligence
- Control and Systems Engineering
- Computational Mechanics
- Co-authors
- Alexander G. SchwingYen‐Yu LinJia‐Bin HuangBing‐Yu ChenHsin‐Yi ChenRaymond A. YehZhongzheng RenLongjiang Zheng
- Topics
- Advanced Image and Video Retrieval Techniques (3 papers)Advanced Neural Network Applications (3 papers)3D Shape Modeling and Analysis (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionEnergy Engineering and Power TechnologyAerospace Engineering
- Journals
- IEEE Transactions on Image ProcessingSustainable Energy Technologies and AssessmentsJournal of Physics Conference Series
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Yuan-Ting Hu
10 papers receiving 118 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 104
- Aerospace Engineering 31
- Artificial Intelligence 18
- Control and Systems Engineering 11
- Computational Mechanics 11
Countries citing papers authored by Yuan-Ting Hu
This map shows the geographic impact of Yuan-Ting Hu'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 Yuan-Ting Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuan-Ting Hu more than expected).
Fields of papers citing papers by Yuan-Ting Hu
This network shows the impact of papers produced by Yuan-Ting Hu. 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 Yuan-Ting Hu. The network helps show where Yuan-Ting Hu may publish in the future.
Co-authorship network of co-authors of Yuan-Ting Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Yuan-Ting Hu. A scholar is included among the top collaborators of Yuan-Ting Hu 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 Yuan-Ting Hu. Yuan-Ting Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 49 | |
| 11 | 12 | |
| 12 | 27 | |
| 13 | 3 |
About Yuan-Ting Hu
Yuan-Ting Hu is a scholar working on Energy Engineering and Power Technology, Computer Vision and Pattern Recognition and Ecological Modeling, having authored 13 papers that have together received 122 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers) and 3D Shape Modeling and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (104 citations), Energy Engineering and Power Technology (5 citations) and Aerospace Engineering (31 citations). Yuan-Ting Hu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Alexander G. Schwing, Yen‐Yu Lin, Jia‐Bin Huang, Bing‐Yu Chen, Hsin‐Yi Chen, Raymond A. Yeh, Zhongzheng Ren, Longjiang Zheng, Xiaoming Zhao and Hao Chen. Their work appears in journals such as IEEE Transactions on Image Processing, Sustainable Energy Technologies and Assessments and Journal of Physics Conference Series.
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.