Mingli Ding

About

Mingli Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Mingli Ding has authored 50 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 9 papers in Media Technology. Recurrent topics in Mingli Ding’s work include Advanced Neural Network Applications (14 papers), Domain Adaptation and Few-Shot Learning (13 papers) and Multimodal Machine Learning Applications (9 papers). Mingli Ding is often cited by papers focused on Advanced Neural Network Applications (14 papers), Domain Adaptation and Few-Shot Learning (13 papers) and Multimodal Machine Learning Applications (9 papers). Mingli Ding collaborates with scholars based in China, Saudi Arabia and Italy. Mingli Ding's co-authors include Aleksandra Pižurica, Xian Li, Guanglei Yang, Yongqiang Zhang, Elisa Ricci, Bernard Ghanem, Yancheng Bai, Hao Tang, Nicu Sebe and Zhengming Ding and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Co-authorship network of co-authors of Mingli Ding i

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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.

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).

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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