Mohammadreza Iman
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- Multimodal Machine Learning Applications 1
- Human Pose and Action Recognition 1
- Advanced Neural Network Applications 1
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning 4
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- COVID-19 diagnosis using AI 4
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- Energy Harvesting in Wireless Networks 1
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- Security in Wireless Sensor Networks 1
- Energy Efficient Wireless Sensor Networks 1
- Co-authors
- Khaled RasheedHamid R. ArabniaIgor Leão dos SantosJohn A. MillerClaudio M. de FariasRobert Maribe BranchFlávia C. DelicatoPaulo F. Pires
- Journals
- SHILAP Revista de lepidopterología (1 paper)arXiv (Cornell University) (1 paper)2021 International Conference on Computational Science and Computational Intelligence (CSCI) (1 paper)
- Partner nations
- United StatesBrazil
In The Last Decade
Mohammadreza Iman
5 papers receiving 340 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 71
- Artificial Intelligence 106
- Health Informatics 4
- Media Technology 21
- Radiology, Nuclear Medicine and Imaging 42
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
The 9 scholars most cited alongside Mohammadreza Iman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A Review of Deep Transfer Learning and Recent Advancementsbreakdown → | 2023 | 337 |
| 2 | 2022 | 2 | |
| 3 | 2022 | 11 | |
| 4 | 2021 | 3 | |
| 5 | 2015 | 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), Energy Harvesting in Wireless Networks (1 paper), Multimodal Machine Learning Applications (1 paper), Human Pose and Action Recognition (1 paper), Security in Wireless Sensor Networks (1 paper), Advanced Neural Network Applications (1 paper) and Energy Efficient Wireless Sensor 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.