Minghao Gou
Impact in
- Human-Computer Interaction top 2%
- Hand Gesture Recognition Systems
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- Robot Manipulation and Learning
- Robotic Mechanisms and Dynamics
Papers in
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- Hand Gesture Recognition Systems 5
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- Robot Manipulation and Learning 7
- Journals
- IEEE Robotics and Automation Letters (1 paper)The International Journal of Robotics Research (1 paper)International Journal of Computer Vision (1 paper)IEEE Transactions on Robotics (1 paper)Journal of Physics Conference Series (1 paper)
In The Last Decade
Minghao Gou
11 papers receiving 761 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Human-Computer Interaction 136
- Control and Systems Engineering 507
- Computer Vision and Pattern Recognition 353
- Artificial Intelligence 188
- Biomedical Engineering 246
Countries citing papers authored by Minghao Gou
This map shows the geographic impact of Minghao Gou'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 Minghao Gou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghao Gou more than expected).
Fields of papers citing papers by Minghao Gou
This network shows the impact of papers produced by Minghao Gou. 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 Minghao Gou. The network helps show where Minghao Gou may publish in the future.
Co-authors
The 25 scholars most cited alongside Minghao Gou, 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 | AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains Hit paper breakdown → | 2023 | 95 |
| 2 | 2023 | 12 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 14 | |
| 5 | 2021 | 33 | |
| 6 | 2021 | 67 | |
| 7 | 2021 | 76 | |
| 8 | 2021 | 0 | |
| 9 | GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping Hit paper breakdown → | 2020 | 353 |
| 10 | 2020 | 1 | |
| 11 | 2019 | 129 | |
| 12 | 2018 | 1 |
About Minghao Gou
Minghao Gou is a scholar working on Human-Computer Interaction, Control and Systems Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering and Signal Processing, having authored 12 papers that have together received 783 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (7 papers), Hand Gesture Recognition Systems (5 papers), Soft Robotics and Applications (4 papers), Human Pose and Action Recognition (2 papers), Advanced Neural Network Applications (2 papers), Modular Robots and Swarm Intelligence (1 paper), Gait Recognition and Analysis (1 paper) and Service-Oriented Architecture and Web Services (1 paper). The work is most often cited by research in Human-Computer Interaction (136 citations), Control and Systems Engineering (507 citations), Computer Vision and Pattern Recognition (353 citations), Artificial Intelligence (188 citations) and Biomedical Engineering (246 citations). Minghao Gou has collaborated with scholars based in China, Germany and Canada. Frequent co-authors include Hao-Shu Fang, Cewu Lu, Chenxi Wang, Hongjie Fang, Jianhua Sun, Runzhong Wang, Yong–Lu Li, Sheng Xu, Jirong Liu and Cewu Lu. Their work appears in journals such as IEEE Robotics and Automation Letters, The International Journal of Robotics Research, International Journal of Computer Vision, IEEE Transactions on Robotics 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.