Rehan Ullah Khan
- Media Technology top 5%
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- Face and Expression Recognition 6
- Video Surveillance and Tracking Methods 6
- Handwritten Text Recognition Techniques 6
- Face recognition and analysis 5
- Obstetrics and Gynecology top 10%
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- Energy Efficient Wireless Sensor Networks 7
- Analytical Chemistry top 10%
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- Machine Learning and Data Classification 6
- Anomaly Detection Techniques and Applications 5
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- Energy Harvesting in Wireless Networks 5
Rehan Ullah Khan
82 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Media Technology 105
- Computer Vision and Pattern Recognition 220
- Obstetrics and Gynecology 74
- Computer Networks and Communications 163
- Analytical Chemistry 51
Countries citing papers authored by Rehan Ullah Khan
This map shows the geographic impact of Rehan Ullah Khan'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 Rehan Ullah Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rehan Ullah Khan more than expected).
Fields of papers citing papers by Rehan Ullah Khan
This network shows the impact of papers produced by Rehan Ullah Khan. 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 Rehan Ullah Khan. The network helps show where Rehan Ullah Khan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rehan Ullah Khan, 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 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | Conventional to Deep Ensemble Methods for Hyperspectral Image Classification: A Comprehensive Surveybreakdown → | 2024 | 54 |
| 4 | 2024 | 4 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 9 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 23 | |
| 13 | 2023 | 1 | |
| 14 | 2022 | 8 | |
| 15 | 2022 | 30 | |
| 16 | 2020 | 23 | |
| 17 | 2020 | 8 | |
| 18 | 2020 | 22 | |
| 19 | 2019 | 23 | |
| 20 | 2019 | 24 |
About Rehan Ullah Khan
Rehan Ullah Khan is a scholar working on Computer Vision and Pattern Recognition, Health Information Management and Artificial Intelligence, having authored 85 papers that have together received 1.1k indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (7 papers), Face and Expression Recognition (6 papers), Video Surveillance and Tracking Methods (6 papers), Machine Learning and Data Classification (6 papers), Handwritten Text Recognition Techniques (6 papers), Energy Harvesting in Wireless Networks (5 papers), Face recognition and analysis (5 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Media Technology (105 citations), Computer Vision and Pattern Recognition (220 citations) and Obstetrics and Gynecology (74 citations). Rehan Ullah Khan has collaborated with scholars based in Saudi Arabia, Pakistan and United Kingdom. Frequent co-authors include Khalil Khan, Ali Mustafa Qamar, Waleed Albattah, Salim El Khediri, Irfan Ullah, Farhan Ullah, Abdennaceur Kachouri, Nejah Nasri, Lunchakorn Wuttisittikulkij and Fan Yang. Their work appears in journals such as PLoS ONE, American Journal of Obstetrics and Gynecology and PLoS Medicine.
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.