Tingting Dan

782 citations
37 papers · 488 · h-index 13

Impact in

Papers in

Tingting Dan

31 papers receiving 480 citations

Peers

Tingting Dan
Comparison fields: 5 of 82
  • Computer Vision and Pattern Recognition 241
  • Media Technology 78
  • Health Informatics 11
  • Radiology, Nuclear Medicine and Imaging 106
  • Otorhinolaryngology 20
Replace Yeqin Shao with:
Yeqin Shao China
Veronika A. Zimmer United Kingdom
Lifang Wei China
Boris Escalante-Ramı́rez Mexico
Ailiang Lin China
Nataša Sladoje Sweden
Mark Eramian Canada
Zhiming Cui China
Puyang Wang United States
Eri Matsuyama Japan
Tingting Dan relative to Yeqin Shao China Yeqin Shao's profile →
Citations per field
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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 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018161
2 202137
3 202329
4 202228
5 202026
6 202124
7 202321
8 202021
9 201819
10 202014
11 202213
12 201913
13 202212
14 20219
15 20189
16 20189
17 20208
18 20207
19 20226
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 37 papers that have together received 488 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Functional Brain Connectivity Studies (6 papers), Advanced Neural Network Applications (5 papers), Remote-Sensing Image Classification (5 papers), Retinal Imaging and Analysis (4 papers), COVID-19 diagnosis using AI (4 papers), Advanced Neuroimaging Techniques and Applications (4 papers) and Medical Image Segmentation Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (241 citations), Media Technology (78 citations), Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (106 citations) and Otorhinolaryngology (20 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, Fei Song, Yue Zhang, Jiao Li, Zhihao Fan and Shengfeng He. Their work appears in journals such as Neurocomputing, Medical Image Analysis, IEEE Transactions on Cybernetics, IEEE Transactions on Medical Imaging and IEEE Access.

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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