Merey Ramazanova
Impact in
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- Plant and animal studies
Papers in
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- Plant and animal studies 1
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- Multimodal Machine Learning Applications 2
- Human Pose and Action Recognition 2
- Co-authors
- Bernard Ghanem (3 shared papers)Salim Al‐Babili (1 shared paper)Matías D. Zurbriggen (1 shared paper)Abrar Felemban (1 shared paper)Boubacar A. Kountche (1 shared paper)Silvio Giancola (1 shared paper)Jian You Wang (1 shared paper)Imran Haider (1 shared paper)
- Journals
- Frontiers in Plant Science (1 paper)PLANT PHYSIOLOGY (1 paper)King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) (2 papers)
- Partner nations
- Saudi ArabiaGermanyKazakhstan
In The Last Decade
Merey Ramazanova
4 papers receiving 39 citations
Peers
Comparison fields: 5 of 20
- Acoustics and Ultrasonics 1
- Ecology, Evolution, Behavior and Systematics 18
- Plant Science 27
- Computer Vision and Pattern Recognition 7
- Analytical Chemistry 2
Countries citing papers authored by Merey Ramazanova
This map shows the geographic impact of Merey Ramazanova'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 Merey Ramazanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Merey Ramazanova more than expected).
Fields of papers citing papers by Merey Ramazanova
This network shows the impact of papers produced by Merey Ramazanova. 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 Merey Ramazanova. The network helps show where Merey Ramazanova may publish in the future.
Co-authors
The 15 scholars most cited alongside Merey Ramazanova, 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 | 2021 | 29 | |
| 2 | 2023 | 5 | |
| 3 | 2023 | 4 | |
| 4 | 2024 | 1 |
About Merey Ramazanova
Merey Ramazanova is a scholar working on Ecology, Evolution, Behavior and Systematics, Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology and Cell Biology, having authored 4 papers that have together received 39 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers), Plant and animal studies (1 paper), Plant Molecular Biology Research (1 paper), Plant Pathogens and Fungal Diseases (1 paper), Plant and Fungal Species Descriptions (1 paper), Plant Parasitism and Resistance (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Acoustics and Ultrasonics (1 citation), Ecology, Evolution, Behavior and Systematics (18 citations), Plant Science (27 citations), Computer Vision and Pattern Recognition (7 citations) and Analytical Chemistry (2 citations). Merey Ramazanova has collaborated with scholars based in Saudi Arabia, Germany and Kazakhstan. Frequent co-authors include Bernard Ghanem, Salim Al‐Babili, Matías D. Zurbriggen, Abrar Felemban, Boubacar A. Kountche, Silvio Giancola, Jian You Wang, Imran Haider, Justine Braguy and Muhammad Jamil. Their work appears in journals such as Frontiers in Plant Science, PLANT PHYSIOLOGY and King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology).
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.