Min Shi
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Media Technology top 10%
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Jiang Yu ZhengYicong ZhouJian WengZunkai HuangJia-Lin ShenLanying LiJiaqi ZhangShuyu Chen
- Topics
- Advanced Vision and Imaging (15 papers)Advanced Image Processing Techniques (9 papers)Video Surveillance and Tracking Methods (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignMedia Technology
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Min Shi
51 papers receiving 319 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 208
- Artificial Intelligence 57
- Media Technology 33
- Electrical and Electronic Engineering 32
- Industrial and Manufacturing Engineering 31
Countries citing papers authored by Min Shi
This map shows the geographic impact of Min Shi'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 Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Shi more than expected).
Fields of papers citing papers by Min Shi
This network shows the impact of papers produced by Min Shi. 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 Shi. The network helps show where Min Shi may publish in the future.
Co-authorship network of co-authors of Min Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Min Shi. A scholar is included among the top collaborators of Min Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Min Shi. Min Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 11 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 22 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 10 | |
| 13 | The Characteristic Study of Pulsed Laser Light Back-scattering of the Simulated Wake Bubbles | 2 |
| 14 | Reduction of blocking artifacts for highly compressed images based on discrete cosine transform domain | 1 |
| 15 | Method of Fault Intelligent Classification Based on Rough Set and Support Vector Machine | 4 |
| 16 | Power quality classification based on rough set and wavelet transform | 1 |
| 17 | Mapping cityscapes into cyberspace for visualization: Research Articles | 3 |
| 18 | 12 | |
| 19 | 1 | |
| 20 | 3 |
About Min Shi
Min Shi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Graphics and Computer-Aided Design, having authored 53 papers that have together received 338 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Advanced Image Processing Techniques (9 papers) and Video Surveillance and Tracking Methods (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (208 citations), Computer Graphics and Computer-Aided Design (23 citations) and Media Technology (33 citations). Min Shi has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Jiang Yu Zheng, Yicong Zhou, Jian Weng, Zunkai Huang, Jia-Lin Shen, Lanying Li, Jiaqi Zhang, Shuyu Chen, Fang‐Lue Zhang and Yu‐Kun Lai. Their work appears in journals such as Water Resources Research, Sensors and International Journal of Computer Vision.
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.