Mingdong Ou
Impact in
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- Complex Network Analysis Techniques
- Artificial Intelligence top 2%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Advanced Image and Video Retrieval Techniques 5
- Multimodal Machine Learning Applications 4
- Video Surveillance and Tracking Methods 3
- Image Retrieval and Classification Techniques 2
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- Complex Network Analysis Techniques 2
- Journals
- IEEE Transactions on Multimedia (1 paper)International Conference on Artificial Intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Mingdong Ou
9 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Statistical and Nonlinear Physics 504
- Artificial Intelligence 680
- Computer Vision and Pattern Recognition 278
- Computational Mathematics 7
- Information Systems 197
Countries citing papers authored by Mingdong Ou
This map shows the geographic impact of Mingdong Ou'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 Mingdong Ou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingdong Ou more than expected).
Fields of papers citing papers by Mingdong Ou
This network shows the impact of papers produced by Mingdong Ou. 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 Mingdong Ou. The network helps show where Mingdong Ou may publish in the future.
Co-authorship network
The 16 scholars most cited alongside Mingdong Ou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 5 | |
| 2 | 2019 | 3 | |
| 3 | Asymmetric Transitivity Preserving Graph Embedding Hit paper breakdown → | 2016 | 716 |
| 4 | Deep multimodal hashing with orthogonal regularization | 2015 | 74 |
| 5 | 2015 | 75 | |
| 6 | 2015 | 9 | |
| 7 | 2015 | 22 | |
| 8 | 2013 | 47 | |
| 9 | 2011 | 95 |
About Mingdong Ou
Mingdong Ou is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Management Science and Operations Research, Information Systems and Artificial Intelligence, having authored 9 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), Multimodal Machine Learning Applications (4 papers), Video Surveillance and Tracking Methods (3 papers), Image Retrieval and Classification Techniques (2 papers), Complex Network Analysis Techniques (2 papers), Advanced Bandit Algorithms Research (2 papers), Expert finding and Q&A systems (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (504 citations), Artificial Intelligence (680 citations), Computer Vision and Pattern Recognition (278 citations), Computational Mathematics (7 citations) and Information Systems (197 citations). Mingdong Ou has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Peng Cui, Wenwu Zhu, Jian Pei, Ziwei Zhang, Daixin Wang, Fei Wang, Shiqiang Yang, Lifeng Sun, Shaowei Liu and Jun Wang. Their work appears in journals such as IEEE Transactions on Multimedia, International Conference on Artificial Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.
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.