Kuan‐Ting Yu
Impact in
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- Robot Manipulation and Learning
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- Robotic Path Planning Algorithms
- Advanced Neural Network Applications
Papers in ⓘ
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- Robot Manipulation and Learning 5
- Machine Fault Diagnosis Techniques 2
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- Industrial Vision Systems and Defect Detection 2
- Co-authors
- Alberto Rodríguez (4 shared papers)Andy Zeng (1 shared paper)Daniel Suo (1 shared paper)Shuran Song (1 shared paper)Jianxiong Xiao (1 shared paper)John J. Leonard (1 shared paper)Li‐Chen Fu (2 shared papers)Pat Marion (1 shared paper)
- Partner nations
- TaiwanUnited StatesGermany
In The Last Decade
Kuan‐Ting Yu
10 papers receiving 474 citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Control and Systems Engineering 316
- Computer Vision and Pattern Recognition 216
- Aerospace Engineering 172
- Human-Computer Interaction 34
- Geology 31
Countries citing papers authored by Kuan‐Ting Yu
This map shows the geographic impact of Kuan‐Ting 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 Kuan‐Ting Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuan‐Ting Yu more than expected).
Fields of papers citing papers by Kuan‐Ting Yu
This network shows the impact of papers produced by Kuan‐Ting 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 Kuan‐Ting Yu. The network helps show where Kuan‐Ting Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kuan‐Ting Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Multi-view self-supervised deep learning for 6D pose estimation in the Amazon Picking Challenge Hit paper breakdown → | 2017 | 303 |
| 2 | 2014 | 91 | |
| 3 | 2010 | 24 | |
| 4 | 2018 | 22 | |
| 5 | 2015 | 19 | |
| 6 | 2018 | 18 | |
| 7 | 2020 | 9 | |
| 8 | 2012 | 5 | |
| 9 | 2024 | 4 | |
| 10 | 2020 | 2 | |
| 11 | 2020 | 0 |
About Kuan‐Ting Yu
Kuan‐Ting Yu is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering, Human-Computer Interaction, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 497 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Robotics and Sensor-Based Localization (4 papers), Gear and Bearing Dynamics Analysis (3 papers), Industrial Vision Systems and Defect Detection (2 papers), Machine Fault Diagnosis Techniques (2 papers), Soft Robotics and Applications (2 papers), Tactile and Sensory Interactions (2 papers) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Control and Systems Engineering (316 citations), Computer Vision and Pattern Recognition (216 citations), Aerospace Engineering (172 citations), Human-Computer Interaction (34 citations) and Geology (31 citations). Kuan‐Ting Yu has collaborated with scholars based in Taiwan, United States and Germany. Frequent co-authors include Alberto Rodríguez, Andy Zeng, Daniel Suo, Shuran Song, Jianxiong Xiao, John J. Leonard, Li‐Chen Fu, Pat Marion, Michael Posa and Hongkai Dai. Their work appears in journals such as IEEE Access, Journal of Field Robotics and Sensors and Materials.
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.