Gavin Weiguang Ding
- Ophthalmology top 5%
- Neurology top 10%
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- Retinal Imaging and Analysis 3
- Medical Imaging Techniques and Applications 1
- Health Information Management top 10%
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- Adversarial Robustness in Machine Learning 4
- Anomaly Detection Techniques and Applications 2
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- Optical Coherence Tomography Applications 3
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- Digital Imaging for Blood Diseases 2
- Medical Image Segmentation Techniques 2
- Digital Image Processing Techniques 1
Gavin Weiguang Ding
11 papers receiving 379 citations
Peers
Comparison fields: 5 of 66
- Ophthalmology 99
- Neurology 77
- Radiology, Nuclear Medicine and Imaging 173
- Health Informatics 7
- Health Information Management 23
Countries citing papers authored by Gavin Weiguang Ding
This map shows the geographic impact of Gavin Weiguang 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 Gavin Weiguang Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Weiguang Ding more than expected).
Fields of papers citing papers by Gavin Weiguang Ding
This network shows the impact of papers produced by Gavin Weiguang 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 Gavin Weiguang Ding. The network helps show where Gavin Weiguang Ding may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Gavin Weiguang Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 22 | |
| 2 | Cascade Dual-branch Deep Neural Networks for Retinal Layer and fluid Segmentation of Optical Coherence Tomography Incorporating Relative Positional Map. | 2020 | 5 |
| 3 | On Minimax Optimality of GANs for Robust Mean Estimation. | 2020 | 3 |
| 4 | 2019 | 113 | |
| 5 | 2019 | 2 | |
| 6 | Max-Margin Adversarial (MMA) Training: Direct Input Space Margin Maximization through Adversarial Training. | 2018 | 10 |
| 7 | Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds | 2018 | 2 |
| 8 | 2018 | 150 | |
| 9 | 2018 | 40 | |
| 10 | Adversarial Robustness of Pruned Neural Networks | 2018 | 14 |
| 11 | 2001 | 26 |
About Gavin Weiguang Ding
Gavin Weiguang Ding is a scholar working on Computer Vision and Pattern Recognition, Orthodontics and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 387 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Retinal Imaging and Analysis (3 papers), Optical Coherence Tomography Applications (3 papers), Digital Imaging for Blood Diseases (2 papers), Medical Image Segmentation Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Digital Image Processing Techniques (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Ophthalmology (99 citations), Neurology (77 citations) and Radiology, Nuclear Medicine and Imaging (173 citations). Gavin Weiguang Ding has collaborated with scholars based in Canada, China and Germany. Frequent co-authors include Donghuan Lu, Mirza Faisal Beg, Karteek Popuri, Rakesh Balachandar, Sieun Lee, Morgan Heisler, Marinko V. Šarunic, Ruitong Huang, Eduardo V. Navajas and Yash Sharma. Their work appears in journals such as Medical Image Analysis, Medical & Biological Engineering & Computing and Computerized Medical Imaging and Graphics.
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.