Min Tan

20.0k citations
691 papers · 15.0k · 1 hit paper · h-index 60

Impact in

Papers in

Min Tan

658 papers receiving 14.7k citations

Min Tan's Hit Papers

MD-YOLO: Multi-scale Dense YOLO for small target pest detection 2023 · 112 citations
1120+1+2Years since publication255075100

Peers

Min Tan
Comparison fields: 5 of 208
  • Ocean Engineering 3.1k
  • Control and Systems Engineering 3.4k
  • Aerospace Engineering 3.6k
  • Developmental Neuroscience 503
  • Computer Vision and Pattern Recognition 2.5k
Replace Cheng Li with:
Cheng Li China
Toshio Fukuda Japan
Max Q.‐H. Meng Hong Kong
Dong Sun Hong Kong
Hongliang Ren Singapore
Karl Johan Åström Sweden
I‐Ming Chen Singapore
Han Wang China
Yong Chen China
Hod Lipson United States
Min Tan relative to Cheng Li China Cheng Li's profile →
Citations per field
00.5×5.4×
Cheng Li · 1×
Citations per year

Countries citing papers authored by Min Tan

Since Specialization
Citations

This map shows the geographic impact of Min Tan'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 Min Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Tan more than expected).

Fields of papers citing papers by Min Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min Tan. 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 Min Tan. The network helps show where Min Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Min Tan, 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 Min Tan Line = papers co-authored together Min Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 691 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004368
2 2009271
3 2008268
4 2005258
5 2013226
6 2015223
7 2009211
8 2009198
9 2013191
10 2011183
11 2002176
12 2011165
13 2013141
14 2018141
15 2003139
16 2011139
17 2019135
18 2006128
19 2015123
20 2013114

About Min Tan

Min Tan is a scholar working on Aerospace Engineering, Ocean Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering and Biomedical Engineering, having authored 691 papers that have together received 15.0k indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (185 papers), Biomimetic flight and propulsion mechanisms (122 papers), Robotics and Sensor-Based Localization (86 papers), Robotic Locomotion and Control (70 papers), Robotic Path Planning Algorithms (63 papers), Distributed Control Multi-Agent Systems (54 papers), Adaptive Control of Nonlinear Systems (53 papers) and Advanced Vision and Imaging (39 papers). The work is most often cited by research in Ocean Engineering (3.1k citations), Control and Systems Engineering (3.4k citations), Aerospace Engineering (3.6k citations), Developmental Neuroscience (503 citations) and Computer Vision and Pattern Recognition (2.5k citations). Min Tan has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Junzhi Yu, Zeng‐Guang Hou, Long Cheng, Zhengxing Wu, Shuo Wang, De Xu, Yu Wang, Jianwei Zhang, Zhiqiang Cao and Rui Wang. Their work appears in journals such as IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Automation Science and Engineering and IEEE Robotics and Automation Letters.

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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