Aydan M. Erkmen
- Control and Systems Engineering top 5%
- Aerospace Engineering top 10%
- Biomedical Engineering
- Mechanical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- İsmet ErkmenÖmer Melih GülBurak KantarcıMehmet Sinan BeksaçH.E. StephanouNazife BaykalR. ChatterjeeTetsushi Kamegawa
- Topics
- Robot Manipulation and Learning (26 papers)Modular Robots and Swarm Intelligence (19 papers)Neural Networks and Applications (16 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionAerospace Engineering
- Partner nations
- TürkiyeUnited StatesJapan
In The Last Decade
Aydan M. Erkmen
98 papers receiving 653 citations
Peers
Comparison fields: 5 of 95
- Control and Systems Engineering 182
- Aerospace Engineering 152
- Biomedical Engineering 150
- Mechanical Engineering 143
- Computer Vision and Pattern Recognition 141
Countries citing papers authored by Aydan M. Erkmen
This map shows the geographic impact of Aydan M. Erkmen'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 Aydan M. Erkmen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aydan M. Erkmen more than expected).
Fields of papers citing papers by Aydan M. Erkmen
This network shows the impact of papers produced by Aydan M. Erkmen. 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 Aydan M. Erkmen. The network helps show where Aydan M. Erkmen may publish in the future.
Co-authorship network of co-authors of Aydan M. Erkmen
This figure shows the co-authorship network connecting the top 25 collaborators of Aydan M. Erkmen. A scholar is included among the top collaborators of Aydan M. Erkmen 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 Aydan M. Erkmen. Aydan M. Erkmen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 42 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | Intelligent health restoration system: reinforcement learning feedback to diagnosis and treatment planning | 2 |
| 9 | 8 | |
| 10 | 8 | |
| 11 | 9 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | Holonic grasping | 4 |
| 15 | 6 | |
| 16 | 32 | |
| 17 | 21 | |
| 18 | A computerized system for the classification of chromosomes based on pattern recognition and image analysis techniques (Çankaya system) | 1 |
| 19 | 2 | |
| 20 | Information fractals for approximate reasoning in sensor-based robot grasp control | 7 |
About Aydan M. Erkmen
Aydan M. Erkmen is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 109 papers that have together received 699 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (26 papers), Modular Robots and Swarm Intelligence (19 papers) and Neural Networks and Applications (16 papers). The work is most often cited by research in Control and Systems Engineering (182 citations), Computer Vision and Pattern Recognition (141 citations) and Aerospace Engineering (152 citations). Aydan M. Erkmen has collaborated with scholars based in Türkiye, United States and Japan. Frequent co-authors include İsmet Erkmen, Ömer Melih Gül, Burak Kantarcı, Mehmet Sinan Beksaç, H.E. Stephanou, Nazife Baykal, R. Chatterjee, Tetsushi Kamegawa, Fumitoshi Matsuno and Akif Durdu. Their work appears in journals such as Sensors, Information Sciences and IEEE Internet of Things Journal.
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.