Minghui Liu
Impact in
- Cognitive Neuroscience top 10%
- Neural and Behavioral Psychology Studies
Papers in
-
- Domain Adaptation and Few-Shot Learning 6
- Co-authors
- Jie Sui (4 shared papers)Carmel Mevorach (1 shared paper)Glyn W. Humphreys (1 shared paper)Jingjing Wang (1 shared paper)Peng Wu (1 shared paper)Zhizhong Dong (1 shared paper)Xiao Dong Chen (1 shared paper)Yong Wang (1 shared paper)
- Journals
- Applied Sciences (4 papers)Frontiers in Oncology (3 papers)Frontiers in Energy Research (2 papers)Journal of Cleaner Production (2 papers)Cancers (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Minghui Liu
88 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 152
- Cognitive Neuroscience 129
- Polymers and Plastics 76
- Experimental and Cognitive Psychology 61
- Automotive Engineering 59
- Energy Engineering and Power Technology 15
Countries citing papers authored by Minghui Liu
This map shows the geographic impact of Minghui Liu'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 Minghui Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghui Liu more than expected).
Fields of papers citing papers by Minghui Liu
This network shows the impact of papers produced by Minghui Liu. 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 Minghui Liu. The network helps show where Minghui Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Minghui Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 113 | |
| 2 | 2019 | 109 | |
| 3 | 2013 | 100 | |
| 4 | 2018 | 86 | |
| 5 | 2016 | 54 | |
| 6 | 2022 | 52 | |
| 7 | 2015 | 42 | |
| 8 | 2009 | 40 | |
| 9 | 2020 | 37 | |
| 10 | 2022 | 35 | |
| 11 | 2023 | 34 | |
| 12 | 2010 | 28 | |
| 13 | 2022 | 24 | |
| 14 | 2023 | 20 | |
| 15 | 2021 | 18 | |
| 16 | 2015 | 17 | |
| 17 | 2022 | 16 | |
| 18 | 2022 | 16 | |
| 19 | 2008 | 15 | |
| 20 | 2016 | 14 |
About Minghui Liu
Minghui Liu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering and Mechanical Engineering, having authored 105 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Domain Adaptation and Few-Shot Learning (6 papers), COVID-19 Clinical Research Studies (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Autonomous Vehicle Technology and Safety (3 papers), Photodynamic Therapy Research Studies (3 papers), Metal-Organic Frameworks: Synthesis and Applications (3 papers) and Face Recognition and Perception (3 papers). The work is most often cited by research in Cognitive Neuroscience (129 citations), Polymers and Plastics (76 citations), Experimental and Cognitive Psychology (61 citations), Automotive Engineering (59 citations) and Energy Engineering and Power Technology (15 citations). Minghui Liu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Jie Sui, Carmel Mevorach, Glyn W. Humphreys, Jingjing Wang, Peng Wu, Zhizhong Dong, Xiao Dong Chen, Yong Wang, Xun He and Nanwen Li. Their work appears in journals such as Applied Sciences, Frontiers in Oncology, Frontiers in Energy Research, Journal of Cleaner Production and Cancers.
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.