Min-Ling Zhang
- Artificial Intelligence top 0.05%
- Computer Vision and Pattern Recognition top 0.1%
- Information Systems top 0.1%
- Molecular Biology top 5%
- Signal Processing top 1%
- Topics
- Text and Document Classification Technologies (93 papers)Image Retrieval and Classification Techniques (41 papers)Machine Learning and Data Classification (32 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsJournal of Membrane Science
- Partner nations
- ChinaUnited StatesChile
In The Last Decade
Min-Ling Zhang
158 papers receiving 10.4k citations
Hit Papers
Peers
Comparison fields: 5 of 200
- Artificial Intelligence 8.3k
- Computer Vision and Pattern Recognition 4.5k
- Information Systems 2.5k
- Molecular Biology 1.7k
- Signal Processing 693
Countries citing papers authored by Min-Ling Zhang
This map shows the geographic impact of Min-Ling Zhang'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-Ling Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min-Ling Zhang more than expected).
Fields of papers citing papers by Min-Ling Zhang
This network shows the impact of papers produced by Min-Ling Zhang. 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-Ling Zhang. The network helps show where Min-Ling Zhang may publish in the future.
Co-authorship network of co-authors of Min-Ling Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Min-Ling Zhang. A scholar is included among the top collaborators of Min-Ling Zhang 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-Ling Zhang. Min-Ling Zhang 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 | 0 | |
| 3 | 0 | |
| 4 | 11 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 10 | |
| 10 | 12 | |
| 11 | 5 | |
| 12 | Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization | 9 |
| 13 | 6 | |
| 14 | Solving the partial label learning problem: an instance-based approach | 77 |
| 15 | Maximum Margin Partial Label Learning | 7 |
| 16 | Classifier Ensemble with Unlabeled Data | 2 |
| 17 | Multi-label learning by instance differentiation | 52 |
| 18 | THE INFLUENCE OF THE THICKNESS OF HOST EGGS CHORION ON THE LONGEVITY AND FECUNDITY OF TRICHOGRAMMA CONFUSUM | 0 |
| 19 | Effects of 14 insecticides on adults, larvae, eggs, and pupae of Trichogramma confusum. | 3 |
| 20 | Rearing of Eocanthecona furcellata | 1 |
About Min-Ling Zhang
Min-Ling Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biological Psychiatry, having authored 177 papers that have together received 10.8k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (93 papers), Image Retrieval and Classification Techniques (41 papers) and Machine Learning and Data Classification (32 papers). The work is most often cited by research in Artificial Intelligence (8.3k citations), Computer Vision and Pattern Recognition (4.5k citations) and Information Systems (2.5k citations). Min-Ling Zhang has collaborated with scholars based in China, United States and Chile. Frequent co-authors include Zhi‐Hua Zhou, Lei Wu, Kun Zhang, Xin Geng, José M. Peña, Vı́ctor Robles, F. Richard Yu, Xuying Liu, Yukun Li and Sheng-Jun Huang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Journal of Membrane Science.
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.