Bin Dong

6.4k citations
119 papers · 3.0k · 1 hit paper · h-index 29

Impact in

Papers in

Bin Dong

111 papers receiving 2.8k citations

Bin Dong's Hit Papers

PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network 2019 · 344 citations
3440+2+4Years since publication100200300

Peers

Bin Dong
Comparison fields: 5 of 146
  • Computer Vision and Pattern Recognition 955
  • Computational Mechanics 781
  • Health Informatics 40
  • Radiology, Nuclear Medicine and Imaging 628
  • Statistical and Nonlinear Physics 366
Replace Peter Maaß with:
Peter Maaß Germany
De-Xing Kong China
Huazhong Shu China
Ben Adcock Canada
Christoph Schnörr Germany
Jérôme Idier France
Ali Mohammad‐Djafari France
Yunjin Chen China
Émilie Chouzenoux France
Mike E. Davies United Kingdom
Bin Dong relative to Peter Maaß Germany Peter Maaß's profile →
Citations per field
00.5×6.7×
Peter Maaß · 1×
Citations per year

Countries citing papers authored by Bin Dong

Since Specialization
Citations

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

Fields of papers citing papers by Bin Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 119 papers — load more, or switch the sort, to bring in the rest.

#Work
1
PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network
Hit paper breakdown →
2019344
2 2012223
3 2010165
4 2022128
5 2011107
6 2020107
7 202087
8 201281
9 200676
10 201274
11 202271
12 201266
13 201160
14 202155
15 202053
16 202152
17 201551
18 201748
19 202147
20 202446

About Bin Dong

Bin Dong is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Artificial Intelligence, having authored 119 papers that have together received 3.0k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (25 papers), Medical Image Segmentation Techniques (18 papers), Medical Imaging Techniques and Applications (18 papers), Sparse and Compressive Sensing Techniques (17 papers), Advanced Image Processing Techniques (11 papers), Model Reduction and Neural Networks (10 papers), Advanced X-ray and CT Imaging (9 papers) and Advanced MRI Techniques and Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (955 citations), Computational Mechanics (781 citations), Health Informatics (40 citations), Radiology, Nuclear Medicine and Imaging (628 citations) and Statistical and Nonlinear Physics (366 citations). Bin Dong has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Zuowei Shen, Yiping Lu, Stanley Osher, Jian‐Feng Cai, Steve Jiang, Xun Jia, Yu Mao, Wotao Yin, Haochen Wang and Gang Wu. Their work appears in journals such as SIAM Journal on Imaging Sciences, Applied and Computational Harmonic Analysis, Journal of Computational Physics, Journal of Scientific Computing and SIAM Journal on Scientific Computing.

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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