Junmo Kim
-
- Advanced Vision and Imaging 30
- Advanced Neural Network Applications 27
- Face and Expression Recognition 24
- Advanced Image and Video Retrieval Techniques 22
- Face recognition and analysis 19
- Multimodal Machine Learning Applications 15
- Video Surveillance and Tracking Methods 14
- Artificial Intelligence top 0.5%
- Domain Adaptation and Few-Shot Learning 30
- Media Technology top 1%
- Human-Computer Interaction top 2%
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceExperimental and Cognitive Psychology
- Journals
- IEEE Access (15 papers)IEEE Transactions on Image Processing (5 papers)International Journal of Technology Management (3 papers)
- Partner nations
- South KoreaCanadaUnited States
In The Last Decade
Junmo Kim
182 papers receiving 4.7k citations
Hit Papers
Peers
Comparison fields: 5 of 184
- Computer Vision and Pattern Recognition 2.9k
- Artificial Intelligence 1.5k
- Experimental and Cognitive Psychology 505
- Media Technology 304
- Human-Computer Interaction 147
Countries citing papers authored by Junmo Kim
This map shows the geographic impact of Junmo 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 Junmo Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junmo Kim more than expected).
Fields of papers citing papers by Junmo Kim
This network shows the impact of papers produced by Junmo 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 Junmo Kim. The network helps show where Junmo Kim may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Junmo Kim, 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 | 2025 | 3 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 8 | |
| 6 | 2024 | 8 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 4 | |
| 10 | 2022 | 7 | |
| 11 | 2021 | 9 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 39 | |
| 14 | 2019 | 9 | |
| 15 | Balancing Domain Gap for Object Instance Detection | 2019 | 1 |
| 16 | 2018 | 2 | |
| 17 | Towards Flatter Loss Surface via Nonmonotonic Learning Rate Scheduling | 2018 | 9 |
| 18 | 2017 | 1 | |
| 19 | Relationship between Ownership Structure and Performance and Value of Korean Pharmaceutical Firms | 2013 | 2 |
| 20 | 2012 | 7 |
About Junmo Kim
Junmo Kim is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 196 papers that have together received 4.8k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (30 papers), Advanced Vision and Imaging (30 papers), Advanced Neural Network Applications (27 papers), Face and Expression Recognition (24 papers), Advanced Image and Video Retrieval Techniques (22 papers), Face recognition and analysis (19 papers), Multimodal Machine Learning Applications (15 papers) and Video Surveillance and Tracking Methods (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.9k citations), Artificial Intelligence (1.5k citations) and Experimental and Cognitive Psychology (505 citations). Junmo Kim has collaborated with scholars based in South Korea, Canada and United States. Frequent co-authors include Junho Yim, Donggyu Joo, Ji‐Hoon Bae, Heechul Jung, Sihaeng Lee, Dongyoon Han, Hansang Lee, Yu‐Wing Tai, Jiwhan Kim and Minseok Park. Their work appears in journals such as IEEE Access, IEEE Transactions on Image Processing, International Journal of Technology Management, ACS Applied Materials & Interfaces and Medical Physics.
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.