Robail Yasrab
Impact in
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- Smart Agriculture and AI
- Plant nutrient uptake and metabolism
- Leaf Properties and Growth Measurement
Papers in
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- Domain Adaptation and Few-Shot Learning 7
- AI in cancer detection 2
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- Fetal and Pediatric Neurological Disorders 10
- Prenatal Screening and Diagnostics 5
- Co-authors
- Michael P. Pound (2 shared papers)Naijie Gu (4 shared papers)Andrew P. French (1 shared paper)Darren M. Wells (1 shared paper)Tony Pridmore (1 shared paper)Jonathan A. Atkinson (1 shared paper)Jincheng Zhang (1 shared paper)J. Alison Noble (11 shared papers)
- Journals
- Applied Sciences (1 paper)Medical Image Analysis (1 paper)GigaScience (1 paper)Ultrasound in Obstetrics and Gynecology (1 paper)Remote Sensing (1 paper)
- Partner nations
- United KingdomChinaIsrael
In The Last Decade
Robail Yasrab
22 papers receiving 304 citations
Peers
Comparison fields: 5 of 78
- Health Informatics 6
- Plant Science 125
- Computer Vision and Pattern Recognition 64
- Neurology 17
- Artificial Intelligence 62
Countries citing papers authored by Robail Yasrab
This map shows the geographic impact of Robail Yasrab'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 Robail Yasrab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robail Yasrab more than expected).
Fields of papers citing papers by Robail Yasrab
This network shows the impact of papers produced by Robail Yasrab. 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 Robail Yasrab. The network helps show where Robail Yasrab may publish in the future.
Co-authors
The 25 scholars most cited alongside Robail Yasrab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 95 | |
| 2 | 2021 | 56 | |
| 3 | 2017 | 30 | |
| 4 | 2022 | 19 | |
| 5 | 2022 | 16 | |
| 6 | 2018 | 15 | |
| 7 | 2021 | 12 | |
| 8 | 2019 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2016 | 9 | |
| 11 | 2023 | 8 | |
| 12 | 2016 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2016 | 6 | |
| 15 | 2022 | 2 | |
| 16 | 2024 | 2 | |
| 17 | 2021 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2023 | 1 |
About Robail Yasrab
Robail Yasrab is a scholar working on Artificial Intelligence, Pediatrics, Perinatology and Child Health, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 25 papers that have together received 314 indexed citations. Recurring topics across this work include Fetal and Pediatric Neurological Disorders (10 papers), Domain Adaptation and Few-Shot Learning (7 papers), Advanced Neural Network Applications (6 papers), Prenatal Screening and Diagnostics (5 papers), Autonomous Vehicle Technology and Safety (2 papers), Multimodal Machine Learning Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (6 citations), Plant Science (125 citations), Computer Vision and Pattern Recognition (64 citations), Neurology (17 citations) and Artificial Intelligence (62 citations). Robail Yasrab has collaborated with scholars based in United Kingdom, China and Israel. Frequent co-authors include Michael P. Pound, Naijie Gu, Andrew P. French, Darren M. Wells, Tony Pridmore, Jonathan A. Atkinson, Jincheng Zhang, J. Alison Noble, Lior Drukker and Aris T. Papageorghiou. Their work appears in journals such as Applied Sciences, Medical Image Analysis, GigaScience, Ultrasound in Obstetrics and Gynecology and Remote Sensing.
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.