B. Uma Shankar
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Media Technology top 1%
- Biomedical Engineering
- Co-authors
- Sankar K. PalSushmita MitraAshish GhoshSaroj K. MeherRalph T. H. LeijenaarChintan ParmarEmmanuel Rios VelazquezM Jermoumi
- Topics
- Remote-Sensing Image Classification (15 papers)Medical Image Segmentation Techniques (7 papers)Image Retrieval and Classification Techniques (7 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Partner nations
- IndiaUnited KingdomJapan
In The Last Decade
B. Uma Shankar
47 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Radiology, Nuclear Medicine and Imaging 530
- Computer Vision and Pattern Recognition 528
- Artificial Intelligence 425
- Media Technology 384
- Biomedical Engineering 211
Countries citing papers authored by B. Uma Shankar
This map shows the geographic impact of B. Uma Shankar'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 B. Uma Shankar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. Uma Shankar more than expected).
Fields of papers citing papers by B. Uma Shankar
This network shows the impact of papers produced by B. Uma Shankar. 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 B. Uma Shankar. The network helps show where B. Uma Shankar may publish in the future.
Co-authorship network of co-authors of B. Uma Shankar
This figure shows the co-authorship network connecting the top 25 collaborators of B. Uma Shankar. A scholar is included among the top collaborators of B. Uma Shankar 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 B. Uma Shankar. B. Uma Shankar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 22 | |
| 5 | 2 | |
| 6 | 34 | |
| 7 | 7 | |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 16 | |
| 11 | 32 | |
| 12 | 31 | |
| 13 | 50 | |
| 14 | Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentationbreakdown → | 468 |
| 15 | 49 | |
| 16 | 11 | |
| 17 | 1 | |
| 18 | 58 | |
| 19 | A New Gray Hough Transform for Region Extraction from IRS Images. | 1 |
| 20 | 2 |
About B. Uma Shankar
B. Uma Shankar is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Health Informatics, having authored 47 papers that have together received 1.6k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (15 papers), Medical Image Segmentation Techniques (7 papers) and Image Retrieval and Classification Techniques (7 papers). The work is most often cited by research in Media Technology (384 citations), Computer Vision and Pattern Recognition (528 citations) and Radiology, Nuclear Medicine and Imaging (530 citations). B. Uma Shankar has collaborated with scholars based in India, United Kingdom and Japan. Frequent co-authors include Sankar K. Pal, Sushmita Mitra, Ashish Ghosh, Saroj K. Meher, Ralph T. H. Leijenaar, Chintan Parmar, Emmanuel Rios Velazquez, M Jermoumi, Philippe Lambin and Sara Carvalho. Their work appears in journals such as PLoS ONE, IEEE Transactions on Geoscience and Remote Sensing and Expert Systems with Applications.
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.