Mingli Ding

2.2k citations
60 papers · 1.1k · h-index 17

Impact in

    • Remote-Sensing Image Classification
    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Video Surveillance and Tracking Methods
    • Multimodal Machine Learning Applications

Papers in

Mingli Ding

56 papers receiving 1.1k citations

Peers

Mingli Ding
Comparison fields: 5 of 91
  • Media Technology 328
  • Computer Vision and Pattern Recognition 702
  • Artificial Intelligence 312
  • Atmospheric Science 114
  • Aerospace Engineering 117
Replace Puhua Chen with:
Puhua Chen China
Lixia Yang China
Jiayuan Fan China
Badri Narayan Subudhi India
Tiecheng Song China
Mingliang Gao China
Xingjia Pan China
Marko Heikkilä Finland
Mingli Ding relative to Puhua Chen China Puhua Chen's profile →
Citations per field
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Puhua Chen · 1×
Citations per year

Countries citing papers authored by Mingli Ding

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Mingli Ding Line = papers co-authored together Mingli Ding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018143
2 2019133
3 2021132
4 201886
5 202049
6 202246
7 202040
8 202330
9 201830
10 202328
11 202128
12 201928
13 200425
14 202223
15 202022
16 201917
17
Transformers Solve the Limited Receptive Field for Monocular Depth Prediction
202116
18 202114
19 202114
20 202114

About Mingli Ding

Mingli Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Media Technology and Control and Systems Engineering, having authored 60 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 (7 papers), Remote-Sensing Image Classification (6 papers), Advanced Image Fusion Techniques (6 papers), Advanced Image Processing Techniques (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Media Technology (328 citations), Computer Vision and Pattern Recognition (702 citations), Artificial Intelligence (312 citations), Atmospheric Science (114 citations) and Aerospace Engineering (117 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.

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