DaeEun Kim
- Biomedical Engineering top 5%
- Cognitive Neuroscience top 5%
- Electrical and Electronic Engineering top 10%
- Polymers and Plastics top 5%
- Mechanical Engineering top 10%
- Co-authors
- Jaehong LeeTaeyoon LeeSeulgee KimSang-Geun LeeRalf MöllerDae‐Eun KimJae‐Kang KimS.A. Al-Sayari
- Topics
- Robotics and Sensor-Based Localization (14 papers)Robotic Path Planning Algorithms (12 papers)Advanced Image and Video Retrieval Techniques (8 papers)
- Journals
- ACS NanoScientific ReportsSmall
- Partner nations
- South KoreaUnited KingdomGermany
In The Last Decade
DaeEun Kim
75 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Biomedical Engineering 899
- Cognitive Neuroscience 490
- Electrical and Electronic Engineering 366
- Polymers and Plastics 333
- Mechanical Engineering 164
Countries citing papers authored by DaeEun Kim
This map shows the geographic impact of DaeEun Kim'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 DaeEun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites DaeEun Kim more than expected).
Fields of papers citing papers by DaeEun Kim
This network shows the impact of papers produced by DaeEun Kim. 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 DaeEun Kim. The network helps show where DaeEun Kim may publish in the future.
Co-authorship network of co-authors of DaeEun Kim
This figure shows the co-authorship network connecting the top 25 collaborators of DaeEun Kim. A scholar is included among the top collaborators of DaeEun Kim 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 DaeEun Kim. DaeEun Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Aerobic exercise attenuates LPS-induced cognitive dysfunction by reducing oxidative stress, glial activation, and neuroinflammationbreakdown → | 64 |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 16 | |
| 6 | 4 | |
| 7 | 11 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | Omni-directional image matching for homing navigation based on optical flow algorithm | 0 |
| 13 | Visual navigation using pixel intensity information | 1 |
| 14 | Finger-gesture Recognition Glove using Velostat (ICCAS 2011) | 22 |
| 15 | Development of Sensor System for Finger Gesture | 1 |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 8 | |
| 20 | An Analysis of Synchrony Conditions for Integrate-and-Fire Neurons | 1 |
About DaeEun Kim
DaeEun Kim is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Human-Computer Interaction, having authored 80 papers that have together received 1.5k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (14 papers), Robotic Path Planning Algorithms (12 papers) and Advanced Image and Video Retrieval Techniques (8 papers). The work is most often cited by research in Cognitive Neuroscience (490 citations), Polymers and Plastics (333 citations) and Biomedical Engineering (899 citations). DaeEun Kim has collaborated with scholars based in South Korea, United Kingdom and Germany. Frequent co-authors include Jaehong Lee, Taeyoon Lee, Seulgee Kim, Sang-Geun Lee, Ralf Möller, Dae‐Eun Kim, Jae‐Kang Kim, S.A. Al-Sayari, Hassan Algadi and Changmin Lee. Their work appears in journals such as ACS Nano, Scientific Reports and Small.
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.