Shahadate Rezvy
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Signal Processing top 10%
- Health Informatics top 5%
- Co-authors
- Tahmina ZebinYuan LuoAboubaker LasebaeMiltos PetridisThierry ChaussaletXiaohong GaoJonathan LooBarbara Braden
- Topics
- Radiomics and Machine Learning in Medical Imaging (2 papers)Advanced MIMO Systems Optimization (2 papers)AI in cancer detection (2 papers)
- Journals
- IEEE Transactions on Information Forensics and SecurityApplied IntelligenceUEA Digital Repository (University of East Anglia)
- Partner nations
- United Kingdom
In The Last Decade
Shahadate Rezvy
8 papers receiving 293 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 213
- Computer Networks and Communications 148
- Radiology, Nuclear Medicine and Imaging 114
- Signal Processing 58
- Health Informatics 30
Countries citing papers authored by Shahadate Rezvy
This map shows the geographic impact of Shahadate Rezvy'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 Shahadate Rezvy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shahadate Rezvy more than expected).
Fields of papers citing papers by Shahadate Rezvy
This network shows the impact of papers produced by Shahadate Rezvy. 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 Shahadate Rezvy. The network helps show where Shahadate Rezvy may publish in the future.
Co-authorship network of co-authors of Shahadate Rezvy
This figure shows the co-authorship network connecting the top 25 collaborators of Shahadate Rezvy. A scholar is included among the top collaborators of Shahadate Rezvy 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 Shahadate Rezvy. Shahadate Rezvy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 93 | |
| 2 | Transfer learning for endoscopy disease detection and segmentation with MASk-RCNN benchmark architecture | 4 |
| 3 | 118 | |
| 4 | Transfer Learning For Endoscopy Disease Detection & Segmentation With Mask-RCNN Benchmark Architecture. | 4 |
| 5 | 74 | |
| 6 | 8 | |
| 7 | 2 | |
| 8 | 2 |
About Shahadate Rezvy
Shahadate Rezvy is a scholar working on Health Information Management, Signal Processing and Gastroenterology, having authored 8 papers that have together received 305 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced MIMO Systems Optimization (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (30 citations), Artificial Intelligence (213 citations) and Computer Networks and Communications (148 citations). Shahadate Rezvy has collaborated with scholars based in United Kingdom. Frequent co-authors include Tahmina Zebin, Yuan Luo, Aboubaker Lasebae, Miltos Petridis, Thierry Chaussalet, Xiaohong Gao, Jonathan Loo, Barbara Braden, Wei Pang and Stephen Taylor. Their work appears in journals such as IEEE Transactions on Information Forensics and Security, Applied Intelligence and UEA Digital Repository (University of East Anglia).
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.