Mohammadreza Iman
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Electrical and Electronic Engineering
- Plant Science
- Co-authors
- Khaled RasheedHamid R. ArabniaIgor Leão dos SantosJohn A. MillerClaudio M. de FariasRobert Maribe BranchFlávia C. DelicatoPaulo F. Pires
- Topics
- COVID-19 diagnosis using AI (4 papers)Domain Adaptation and Few-Shot Learning (4 papers)Energy Harvesting in Wireless Networks (1 paper)
- Journals
- SHILAP Revista de lepidopterologíaarXiv (Cornell University)2021 International Conference on Computational Science and Computational Intelligence (CSCI)
- Partner nations
- United StatesBrazil
In The Last Decade
Mohammadreza Iman
5 papers receiving 340 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 106
- Computer Vision and Pattern Recognition 71
- Radiology, Nuclear Medicine and Imaging 42
- Electrical and Electronic Engineering 34
- Plant Science 30
Countries citing papers authored by Mohammadreza Iman
This map shows the geographic impact of Mohammadreza Iman'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 Mohammadreza Iman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammadreza Iman more than expected).
Fields of papers citing papers by Mohammadreza Iman
This network shows the impact of papers produced by Mohammadreza Iman. 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 Mohammadreza Iman. The network helps show where Mohammadreza Iman may publish in the future.
Co-authorship network of co-authors of Mohammadreza Iman
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammadreza Iman. A scholar is included among the top collaborators of Mohammadreza Iman 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 Mohammadreza Iman. Mohammadreza Iman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Review of Deep Transfer Learning and Recent Advancementsbreakdown → | 337 |
| 2 | 2 | |
| 3 | 11 | |
| 4 | 3 | |
| 5 | 2 |
About Mohammadreza Iman
Mohammadreza Iman is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 5 papers that have together received 355 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Energy Harvesting in Wireless Networks (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (106 citations) and Health Informatics (4 citations). Mohammadreza Iman has collaborated with scholars based in United States and Brazil. Frequent co-authors include Khaled Rasheed, Hamid R. Arabnia, Igor Leão dos Santos, John A. Miller, Claudio M. de Farias, Robert Maribe Branch, Flávia C. Delicato, Paulo F. Pires and Luci Pìrmez. Their work appears in journals such as SHILAP Revista de lepidopterología, arXiv (Cornell University) and 2021 International Conference on Computational Science and Computational Intelligence (CSCI).
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.