Mingli Ding
- Media Technology top 1%
- Advanced Image Fusion Techniques 6
- Remote-Sensing Image Classification 6
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- Advanced Neural Network Applications 18
- Multimodal Machine Learning Applications 11
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 16
- Atmospheric Science top 10%
- Aerospace Engineering top 10%
- Inertial Sensor and Navigation 9
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- Advanced Algorithms and Applications 6
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- COVID-19 diagnosis using AI 5
- Co-authors
- Yongqiang ZhangYancheng BaiBernard GhanemAleksandra PižuricaXian LiGuanglei YangElisa RicciHao Tang
- Journals
- Pattern Recognition (5 papers)Applied Intelligence (4 papers)IEEE Transactions on Geoscience and Remote Sensing (3 papers)
- Partner nations
- ChinaSaudi ArabiaBelgium
In The Last Decade
Mingli Ding
61 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 91
- Media Technology 322
- Computer Vision and Pattern Recognition 690
- Artificial Intelligence 307
- Atmospheric Science 114
- Aerospace Engineering 123
Countries citing papers authored by Mingli Ding
This map shows the geographic impact of Mingli Ding'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 Mingli Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingli Ding more than expected).
Fields of papers citing papers by Mingli Ding
This network shows the impact of papers produced by Mingli Ding. 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 Mingli Ding. The network helps show where Mingli Ding may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mingli Ding, 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 | 2024 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 0 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 24 | |
| 8 | 2022 | 23 | |
| 9 | 2022 | 47 | |
| 10 | 2021 | 128 | |
| 11 | Transformers Solve the Limited Receptive Field for Monocular Depth Prediction | 2021 | 16 |
| 12 | 2021 | 3 | |
| 13 | 2019 | 1 | |
| 14 | 2019 | 8 | |
| 15 | 2018 | 85 | |
| 16 | 2015 | 3 | |
| 17 | 2015 | 2 | |
| 18 | Experimental research for propagation of acoustic emission signals across composites | 2012 | 1 |
| 19 | 2010 | 3 | |
| 20 | Research on Changes of Trace Components in Fermentation of Yellow Rice Wine | 2001 | 2 |
About Mingli Ding
Mingli Ding is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Aerospace Engineering and Control and Systems Engineering, having authored 65 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (18 papers), Domain Adaptation and Few-Shot Learning (16 papers), Multimodal Machine Learning Applications (11 papers), Inertial Sensor and Navigation (9 papers), Advanced Image Fusion Techniques (6 papers), Remote-Sensing Image Classification (6 papers), Advanced Algorithms and Applications (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Media Technology (322 citations), Computer Vision and Pattern Recognition (690 citations), Artificial Intelligence (307 citations), Atmospheric Science (114 citations) and Aerospace Engineering (123 citations). Mingli Ding has collaborated with scholars based in China, Saudi Arabia and Belgium. Frequent co-authors include Yongqiang Zhang, Yancheng Bai, Bernard Ghanem, Aleksandra Pižurica, Xian Li, Guanglei Yang, Elisa Ricci, Hao Tang, Nicu Sebe and Yongqiang Li. Their work appears in journals such as Pattern Recognition, Applied Intelligence, IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Neural Networks and Learning Systems 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.