A. K. Gupta
- Computer Vision and Pattern Recognition top 10%
- Statistics and Probability top 5%
- Artificial Intelligence top 10%
- Cardiology and Cardiovascular Medicine
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Jie ChenDorin ComaniciuXiang Sean ZhouBogdan GeorgescuDaya K. NagarD. G. KabeS. Ejaz AhmedAnte Harxhi
- Topics
- Medical Image Segmentation Techniques (3 papers)Scientific Research and Discoveries (2 papers)Blood Pressure and Hypertension Studies (1 paper)
- Cited by
- Statistics and ProbabilityComputer Vision and Pattern RecognitionStatistics, Probability and Uncertainty
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceProceedings of the American Mathematical SocietyAnnals of the Institute of Statistical Mathematics
- Partner nations
- United StatesCanadaIndia
In The Last Decade
A. K. Gupta
9 papers receiving 420 citations
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 130
- Statistics and Probability 130
- Artificial Intelligence 95
- Cardiology and Cardiovascular Medicine 50
- Radiology, Nuclear Medicine and Imaging 49
Countries citing papers authored by A. K. Gupta
This map shows the geographic impact of A. K. Gupta'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 A. K. Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. K. Gupta more than expected).
Fields of papers citing papers by A. K. Gupta
This network shows the impact of papers produced by A. K. Gupta. 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 A. K. Gupta. The network helps show where A. K. Gupta may publish in the future.
Co-authorship network of co-authors of A. K. Gupta
This figure shows the co-authorship network connecting the top 25 collaborators of A. K. Gupta. A scholar is included among the top collaborators of A. K. Gupta 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 A. K. Gupta. A. K. Gupta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 85 | |
| 3 | 83 | |
| 4 | 3 | |
| 5 | 7 | |
| 6 | 224 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 11 | |
| 10 | 13 |
About A. K. Gupta
A. K. Gupta is a scholar working on Family Practice, Statistics and Probability and Modeling and Simulation, having authored 10 papers that have together received 432 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (3 papers), Scientific Research and Discoveries (2 papers) and Blood Pressure and Hypertension Studies (1 paper). The work is most often cited by research in Statistics and Probability (130 citations), Computer Vision and Pattern Recognition (130 citations) and Statistics, Probability and Uncertainty (45 citations). A. K. Gupta has collaborated with scholars based in United States, Canada and India. Frequent co-authors include Jie Chen, Dorin Comaniciu, Xiang Sean Zhou, Bogdan Georgescu, Daya K. Nagar, D. G. Kabe, S. Ejaz Ahmed, Ante Harxhi and Simrati Kaul. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the American Mathematical Society and Annals of the Institute of Statistical Mathematics.
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.