Suranjana Samanta
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Media Technology top 10%
- Signal Processing
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Sukhendu DasJianyong JiangKoshy VargheseJoseph A. O’SullivanYuan‐Chuan TaiSamik BanerjeeShashank MujumdarStanisław Majewski
- Topics
- Domain Adaptation and Few-Shot Learning (8 papers)Medical Imaging Techniques and Applications (5 papers)Face and Expression Recognition (4 papers)
- Partner nations
- IndiaUnited StatesCanada
In The Last Decade
Suranjana Samanta
20 papers receiving 275 citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 117
- Artificial Intelligence 93
- Media Technology 38
- Signal Processing 35
- Radiology, Nuclear Medicine and Imaging 34
Countries citing papers authored by Suranjana Samanta
This map shows the geographic impact of Suranjana Samanta'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 Suranjana Samanta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suranjana Samanta more than expected).
Fields of papers citing papers by Suranjana Samanta
This network shows the impact of papers produced by Suranjana Samanta. 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 Suranjana Samanta. The network helps show where Suranjana Samanta may publish in the future.
Co-authorship network of co-authors of Suranjana Samanta
This figure shows the co-authorship network connecting the top 25 collaborators of Suranjana Samanta. A scholar is included among the top collaborators of Suranjana Samanta 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 Suranjana Samanta. Suranjana Samanta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 6 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 5 | |
| 18 | 223 | |
| 19 | 10 | |
| 20 | 2 |
About Suranjana Samanta
Suranjana Samanta is a scholar working on Radiation, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 284 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (8 papers), Medical Imaging Techniques and Applications (5 papers) and Face and Expression Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Media Technology (38 citations) and Signal Processing (35 citations). Suranjana Samanta has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Sukhendu Das, Jianyong Jiang, Koshy Varghese, Joseph A. O’Sullivan, Yuan‐Chuan Tai, Samik Banerjee, Shashank Mujumdar, Stanisław Majewski, M. Schmand and Robert A. Mintzer. Their work appears in journals such as IEEE Transactions on Medical Imaging, Physics in Medicine and Biology and IET Image Processing.
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.