Ming Xiang
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computer Networks and Communications
- Computational Mechanics
- Media Technology top 10%
- Co-authors
- Yupei ZhangBo YangFang WenChongzhao HanFangyun WeiTing ZhangChen DongNanning Zheng
- Topics
- Distributed Sensor Networks and Detection Algorithms (9 papers)Target Tracking and Data Fusion in Sensor Networks (9 papers)Face and Expression Recognition (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionNeurocomputing
- Partner nations
- China
In The Last Decade
Ming Xiang
21 papers receiving 240 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 144
- Artificial Intelligence 93
- Computer Networks and Communications 43
- Computational Mechanics 42
- Media Technology 36
Countries citing papers authored by Ming Xiang
This map shows the geographic impact of Ming Xiang'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 Ming Xiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Xiang more than expected).
Fields of papers citing papers by Ming Xiang
This network shows the impact of papers produced by Ming Xiang. 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 Ming Xiang. The network helps show where Ming Xiang may publish in the future.
Co-authorship network of co-authors of Ming Xiang
This figure shows the co-authorship network connecting the top 25 collaborators of Ming Xiang. A scholar is included among the top collaborators of Ming Xiang 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 Ming Xiang. Ming Xiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 13 | |
| 3 | 23 | |
| 4 | 6 | |
| 5 | 56 | |
| 6 | 2 | |
| 7 | 21 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | Fingerprint Image Enhancement and Minutiae Extraction | 14 |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 2 | |
| 17 | Optimum Detection Fusion Algorithm for Distributed and Quantized Neyman-Pearson Detection Systems | 1 |
| 18 | Detection Fusion Algorithm for Distributed Neyman-Pearson Detection Systems with Serial Structures | 0 |
| 19 | 3 | |
| 20 | 22 |
About Ming Xiang
Ming Xiang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 24 papers that have together received 249 indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (9 papers), Target Tracking and Data Fusion in Sensor Networks (9 papers) and Face and Expression Recognition (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (144 citations), Media Technology (36 citations) and Signal Processing (33 citations). Ming Xiang has collaborated with scholars based in China. Frequent co-authors include Yupei Zhang, Bo Yang, Fang Wen, Chongzhao Han, Fangyun Wei, Ting Zhang, Chen Dong, Nanning Zheng, Dong Chen and Jing Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Neurocomputing.
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.