Seba Susan
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Media Technology top 2%
- Information Systems top 10%
- Co-authors
- Srishti VashishthaManisha SainiM. HanmandluAmitesh KumarMonika SharmaOm Prakash VermaPuneet JainVamsi Krishna Madasu
- Topics
- Image Retrieval and Classification Techniques (22 papers)Face and Expression Recognition (14 papers)Text and Document Classification Technologies (11 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsNeurocomputing
In The Last Decade
Seba Susan
94 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 132
- Artificial Intelligence 707
- Computer Vision and Pattern Recognition 447
- Radiology, Nuclear Medicine and Imaging 190
- Media Technology 145
- Information Systems 106
Countries citing papers authored by Seba Susan
This map shows the geographic impact of Seba Susan'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 Seba Susan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seba Susan more than expected).
Fields of papers citing papers by Seba Susan
This network shows the impact of papers produced by Seba Susan. 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 Seba Susan. The network helps show where Seba Susan may publish in the future.
Co-authorship network of co-authors of Seba Susan
This figure shows the co-authorship network connecting the top 25 collaborators of Seba Susan. A scholar is included among the top collaborators of Seba Susan 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 Seba Susan. Seba Susan 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 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 9 | |
| 14 | 4 | |
| 15 | 44 | |
| 16 | 56 | |
| 17 | 8 | |
| 18 | 14 | |
| 19 | 5 | |
| 20 | Auto-segmentation using mean-shift and entropy analysis | 8 |
About Seba Susan
Seba Susan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 105 papers that have together received 1.3k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (22 papers), Face and Expression Recognition (14 papers) and Text and Document Classification Technologies (11 papers). The work is most often cited by research in Artificial Intelligence (707 citations), Computer Vision and Pattern Recognition (447 citations) and Media Technology (145 citations). Seba Susan has collaborated with scholars based in India and Australia. Frequent co-authors include Srishti Vashishtha, Manisha Saini, M. Hanmandlu, Amitesh Kumar, Monika Sharma, Om Prakash Verma, Puneet Jain, Vamsi Krishna Madasu, Prachi Agrawal and Muralidhar Kulkarni. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Neurocomputing.
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.