Songde Ma
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Media Technology top 5%
- Signal Processing top 10%
- Global and Planetary Change
- Co-authors
- De-Shuang HuangHanqing LuJing LiuQingshan LiuMingjing LiZhaohui ZhangWei FuV. Prinet
- Topics
- Advanced Image and Video Retrieval Techniques (8 papers)Medical Image Segmentation Techniques (6 papers)Image and Object Detection Techniques (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingPattern Recognition
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Songde Ma
39 papers receiving 462 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 352
- Artificial Intelligence 133
- Media Technology 64
- Signal Processing 49
- Global and Planetary Change 27
Countries citing papers authored by Songde Ma
This map shows the geographic impact of Songde Ma'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 Songde Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Songde Ma more than expected).
Fields of papers citing papers by Songde Ma
This network shows the impact of papers produced by Songde Ma. 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 Songde Ma. The network helps show where Songde Ma may publish in the future.
Co-authorship network of co-authors of Songde Ma
This figure shows the co-authorship network connecting the top 25 collaborators of Songde Ma. A scholar is included among the top collaborators of Songde Ma 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 Songde Ma. Songde Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 11 | |
| 3 | 5 | |
| 4 | 7 | |
| 5 | SAR Image De-speckling Based on Modified Frost Filter | 1 |
| 6 | 10 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 9 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 81 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 4 |
About Songde Ma
Songde Ma is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 39 papers that have together received 483 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Medical Image Segmentation Techniques (6 papers) and Image and Object Detection Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (352 citations), Media Technology (64 citations) and Signal Processing (49 citations). Songde Ma has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include De-Shuang Huang, Hanqing Lu, Jing Liu, Qingshan Liu, Mingjing Li, Zhaohui Zhang, Hanqing Lu, Wei Fu, V. Prinet and Jinqiao Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.
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.