Gang Sun
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.5%
- Media Technology top 0.2%
- Radiology, Nuclear Medicine and Imaging top 1%
- Biomedical Engineering top 5%
- Topics
- Domain Adaptation and Few-Shot Learning (6 papers)Advanced Image and Video Retrieval Techniques (4 papers)Advanced Neural Network Applications (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaMacaoUnited Kingdom
In The Last Decade
Gang Sun
18 papers receiving 8.4k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Computer Vision and Pattern Recognition 4.9k
- Artificial Intelligence 2.1k
- Media Technology 1.3k
- Radiology, Nuclear Medicine and Imaging 1.0k
- Biomedical Engineering 726
Countries citing papers authored by Gang Sun
This map shows the geographic impact of Gang Sun'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 Gang Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gang Sun more than expected).
Fields of papers citing papers by Gang Sun
This network shows the impact of papers produced by Gang Sun. 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 Gang Sun. The network helps show where Gang Sun may publish in the future.
Co-authorship network of co-authors of Gang Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Gang Sun. A scholar is included among the top collaborators of Gang Sun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gang Sun. Gang Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 15 | |
| 5 | 13 | |
| 6 | 2 | |
| 7 | 66 | |
| 8 | Squeeze-and-Excitation Networksbreakdown → | 8158 |
| 9 | Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks | 88 |
| 10 | 7 | |
| 11 | 167 | |
| 12 | 43 | |
| 13 | 11 | |
| 14 | 4 | |
| 15 | A Low Cost 3D Acquiring System for Mushroom Robot Based on Webcam and Line Laser | 3 |
| 16 | 40 | |
| 17 | 3 | |
| 18 | Preliminary Studies on Soil Animals in a Ragweed Habitat | 1 |
About Gang Sun
Gang Sun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 18 papers that have together received 8.6k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (4.9k citations), Media Technology (1.3k citations) and Artificial Intelligence (2.1k citations). Gang Sun has collaborated with scholars based in China, Macao and United Kingdom. Frequent co-authors include Jie Hu, Li Shen, Samuel Albanie, Enhua Wu, Xudong Cao, Yu Qiao, Andrea Vedaldi, Shuhui Wang, Qingming Huang and Li Shen. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.