Shenglin Mu
-
- Robotic Path Planning Algorithms 6
- Video Surveillance and Tracking Methods 4
- Control and Systems Engineering top 10%
- Piezoelectric Actuators and Control 16
- Iterative Learning Control Systems 12
- Advanced Control Systems Design 6
- Robotics and Automated Systems 5
- Artificial Intelligence top 10%
- Anomaly Detection Techniques and Applications 4
- Media Technology top 10%
-
- Gaze Tracking and Assistive Technology 4
- Co-authors
- Seiichi SerikawaHuimin LuDong WangHyoung Seop KimYujie LiKanya TanakaShota NakashimaTomonori YAMAMOTO
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterología (3 papers)IEEE Access (1 paper)Sensors (1 paper)
- Partner nations
- JapanChinaUnited States
In The Last Decade
Shenglin Mu
45 papers receiving 558 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 171
- Control and Systems Engineering 128
- Artificial Intelligence 159
- Renewable Energy, Sustainability and the Environment 64
- Media Technology 31
Countries citing papers authored by Shenglin Mu
This map shows the geographic impact of Shenglin Mu'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 Shenglin Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shenglin Mu more than expected).
Fields of papers citing papers by Shenglin Mu
This network shows the impact of papers produced by Shenglin Mu. 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 Shenglin Mu. The network helps show where Shenglin Mu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shenglin Mu, 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 | 2023 | 2 | |
| 2 | 2022 | 3 | |
| 3 | 2022 | 69 | |
| 4 | 2022 | 0 | |
| 5 | 2020 | 2 | |
| 6 | 2020 | 4 | |
| 7 | 2020 | 3 | |
| 8 | 2019 | 0 | |
| 9 | 2019 | 2 | |
| 10 | 2019 | 5 | |
| 11 | Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learningbreakdown → | 2017 | 336 |
| 12 | 2016 | 2 | |
| 13 | 2015 | 1 | |
| 14 | 2014 | 12 | |
| 15 | 2014 | 1 | |
| 16 | 2014 | 2 | |
| 17 | 2014 | 1 | |
| 18 | 2013 | 1 | |
| 19 | 2013 | 8 | |
| 20 | Intelligent IMC-PID control for ultrasonic motor | 2009 | 1 |
About Shenglin Mu
Shenglin Mu is a scholar working on Human-Computer Interaction, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 569 indexed citations. Recurring topics across this work include Piezoelectric Actuators and Control (16 papers), Iterative Learning Control Systems (12 papers), Advanced Control Systems Design (6 papers), Robotic Path Planning Algorithms (6 papers), Robotics and Automated Systems (5 papers), Video Surveillance and Tracking Methods (4 papers), Anomaly Detection Techniques and Applications (4 papers) and Gaze Tracking and Assistive Technology (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (171 citations), Control and Systems Engineering (128 citations) and Artificial Intelligence (159 citations). Shenglin Mu has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Seiichi Serikawa, Huimin Lu, Dong Wang, Hyoung Seop Kim, Yujie Li, Kanya Tanaka, Shota Nakashima, Tomonori YAMAMOTO, Hui Xu and Wei Zeng. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.
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.