Tingting Dan

753 citations
34 papers · 474 · h-index 13

Impact in

Papers in

Tingting Dan

28 papers receiving 467 citations

Peers

Tingting Dan
Comparison fields: 5 of 81
  • Computer Vision and Pattern Recognition 240
  • Health Informatics 14
  • Media Technology 79
  • Radiology, Nuclear Medicine and Imaging 123
  • Otorhinolaryngology 21
Replace Yeqin Shao with:
Yeqin Shao China
Jianan Chen China
Eri Matsuyama Japan
Sharib Ali United Kingdom
Veronika A. Zimmer United Kingdom
Itsuo Kumazawa Japan
Boris Escalante‐Ramírez Mexico
Zhiming Cui China
Puyang Wang United States
Tingting Dan relative to Yeqin Shao China Yeqin Shao's profile →
Citations per field
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Yeqin Shao · 1×
Citations per year

Countries citing papers authored by Tingting Dan

Since Specialization
Citations

This map shows the geographic impact of Tingting Dan'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 Tingting Dan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tingting Dan more than expected).

Fields of papers citing papers by Tingting Dan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tingting Dan. 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 Tingting Dan. The network helps show where Tingting Dan may publish in the future.

Co-authors

The 25 scholars most cited alongside Tingting Dan, 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 Tingting Dan Line = papers co-authored together Tingting Dan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018159
2 202137
3 202227
4 202026
5 202326
6 202124
7 202021
8 202319
9 201819
10 201913
11 202013
12 202212
13 202212
14 20189
15 20219
16 20189
17 20208
18 20207
19 20225
20 20205

About Tingting Dan

Tingting Dan is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Artificial Intelligence and Media Technology, having authored 34 papers that have together received 474 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Advanced Neural Network Applications (5 papers), Remote-Sensing Image Classification (5 papers), Functional Brain Connectivity Studies (5 papers), Advanced Neuroimaging Techniques and Applications (4 papers), COVID-19 diagnosis using AI (4 papers), Retinal Imaging and Analysis (4 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (240 citations), Health Informatics (14 citations), Media Technology (79 citations), Radiology, Nuclear Medicine and Imaging (123 citations) and Otorhinolaryngology (21 citations). Tingting Dan has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Yang Yang, Zhuoqian Yang, Hongmin Cai, Xijie Chen, Hong Peng, Yue Zhang, Fei Song, Zhihao Fan, Shengfeng He and Jiao Li. Their work appears in journals such as Neurocomputing, IEEE Transactions on Cybernetics, IEEE Access, IEEE Transactions on Medical Imaging and Medical Image Analysis.

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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