Junyeong Kim
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Co-authors
- Chang D. YooTrung X. PhamJae Hyun HanSunghun KangHee Seung WangYoung-Hoon JungKeon Jae LeeHyunsin Park
- Topics
- Multimodal Machine Learning Applications (11 papers)Human Pose and Action Recognition (9 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Journals
- Advanced MaterialsIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Access
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Junyeong Kim
16 papers receiving 458 citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Biomedical Engineering 251
- Computer Vision and Pattern Recognition 146
- Cognitive Neuroscience 97
- Artificial Intelligence 97
- Electrical and Electronic Engineering 88
Countries citing papers authored by Junyeong Kim
This map shows the geographic impact of Junyeong 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 Junyeong Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junyeong Kim more than expected).
Fields of papers citing papers by Junyeong Kim
This network shows the impact of papers produced by Junyeong 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 Junyeong Kim. The network helps show where Junyeong Kim may publish in the future.
Co-authorship network of co-authors of Junyeong Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Junyeong Kim. A scholar is included among the top collaborators of Junyeong 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 Junyeong Kim. Junyeong 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 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 11 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 3 | |
| 13 | 15 | |
| 14 | 55 | |
| 15 | 13 | |
| 16 | Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processingbreakdown → | 288 |
| 17 | 3 | |
| 18 | 50 | |
| 19 | 0 | |
| 20 | 4 |
About Junyeong Kim
Junyeong Kim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 23 papers that have together received 469 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (11 papers), Human Pose and Action Recognition (9 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (146 citations), Biomedical Engineering (251 citations) and Polymers and Plastics (74 citations). Junyeong Kim has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Chang D. Yoo, Trung X. Pham, Jae Hyun Han, Sunghun Kang, Hee Seung Wang, Young-Hoon Jung, Keon Jae Lee, Hyunsin Park, Seong Kwang Hong and Kyungsu Kim. Their work appears in journals such as Advanced Materials, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.
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.