Yuan-Ting Hu

559 citations
13 papers · 122 · h-index 6

Impact in

Papers in

Yuan-Ting Hu

10 papers receiving 118 citations

Peers

Yuan-Ting Hu
Comparison fields: 5 of 38
  • Computer Vision and Pattern Recognition 104
  • Energy Engineering and Power Technology 5
  • Aerospace Engineering 31
  • Human-Computer Interaction 5
  • Computer Graphics and Computer-Aided Design 2
Replace Kirsty Ellis with:
Kirsty Ellis United Kingdom
Sudeep Pillai United States
Claus Gramkow Denmark
Yifu Zhang United States
L. Yan China
Keerthana Gopalakrishnan United States
Nur Muhammad Mahi Shafiullah United States
V. Vaquero Spain
Sanyi Zhang China
Shenyuan Gao Hong Kong
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Citations per field
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Citations per year

Countries citing papers authored by Yuan-Ting Hu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 23 scholars most cited alongside Yuan-Ting Hu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yuan-Ting Hu Line = papers co-authored together Yuan-Ting Hu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201949
2 201527
3 201612
4 20238
5 20217
6 20227
7 20195
8 20093
9 20223
10 20211
11 20240
12 20230
13 20220

About Yuan-Ting Hu

Yuan-Ting Hu is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computational Mechanics, Control and Systems Engineering and Energy Engineering and Power Technology, having authored 13 papers that have together received 122 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Human Pose and Action Recognition (2 papers), Power Systems and Renewable Energy (2 papers), Advanced Vision and Imaging (2 papers), Microgrid Control and Optimization (2 papers) and High-Voltage Power Transmission Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (104 citations), Energy Engineering and Power Technology (5 citations), Aerospace Engineering (31 citations), Human-Computer Interaction (5 citations) and Computer Graphics and Computer-Aided Design (2 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 Haozhe Huang. Their work appears in journals such as IEEE Transactions on Image Processing, Sustainable Energy Technologies and Assessments, Journal of Physics Conference Series, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

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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