Geonmo Gu
Impact in
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- Graph Theory and Algorithms
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Face recognition and analysis
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
Papers in
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- Advanced Image and Video Retrieval Techniques 6
- Multimodal Machine Learning Applications 4
- Graph Theory and Algorithms 3
- Face recognition and analysis 3
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- Domain Adaptation and Few-Shot Learning 5
- Advanced Graph Neural Networks 3
- Algorithms and Data Compression 2
- Co-authors
- Byungsoo Ko (7 shared papers)Kunsoo Park (5 shared papers)Wook-Shin Han (3 shared papers)Hyunjoon Kim (1 shared paper)Minchul Shin (1 shared paper)Sung‐Hyun Lee (1 shared paper)Nam Ik Cho (1 shared paper)Paolo Lunghi (1 shared paper)
- Journals
- Theoretical Computer Science (1 paper)Acta Astronautica (1 paper)Lecture notes in computer science (3 papers)IRIS - Institutional Research Information System (Libera Università Internazionale degli Studi Sociali Guido Carli) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (3 papers)
- Partner nations
- South KoreaItalyUnited States
In The Last Decade
Geonmo Gu
14 papers receiving 352 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 280
- Artificial Intelligence 194
- Signal Processing 45
- Hardware and Architecture 21
- Geology 9
Countries citing papers authored by Geonmo Gu
This map shows the geographic impact of Geonmo Gu'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 Geonmo Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geonmo Gu more than expected).
Fields of papers citing papers by Geonmo Gu
This network shows the impact of papers produced by Geonmo Gu. 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 Geonmo Gu. The network helps show where Geonmo Gu may publish in the future.
Co-authors
The 22 scholars most cited alongside Geonmo Gu, 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 | 2019 | 122 | |
| 2 | 2022 | 52 | |
| 3 | 2020 | 36 | |
| 4 | 2021 | 28 | |
| 5 | 2022 | 24 | |
| 6 | 2020 | 18 | |
| 7 | 2021 | 18 | |
| 8 | 2024 | 17 | |
| 9 | 2023 | 17 | |
| 10 | 2020 | 11 | |
| 11 | 2017 | 7 | |
| 12 | 2022 | 5 | |
| 13 | 2021 | 3 | |
| 14 | 2016 | 3 | |
| 15 | 2022 | 0 |
About Geonmo Gu
Geonmo Gu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Hardware and Architecture and Aerospace Engineering, having authored 15 papers that have together received 361 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers), Graph Theory and Algorithms (3 papers), Face recognition and analysis (3 papers), Advanced Graph Neural Networks (3 papers), Network Packet Processing and Optimization (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (280 citations), Artificial Intelligence (194 citations), Signal Processing (45 citations), Hardware and Architecture (21 citations) and Geology (9 citations). Geonmo Gu has collaborated with scholars based in South Korea, Italy and United States. Frequent co-authors include Byungsoo Ko, Kunsoo Park, Wook-Shin Han, Hyunjoon Kim, Minchul Shin, Sung‐Hyun Lee, Nam Ik Cho, Paolo Lunghi, Michèle Lavagna and Sanghyuk Chun. Their work appears in journals such as Theoretical Computer Science, Acta Astronautica, Lecture notes in computer science, IRIS - Institutional Research Information System (Libera Università Internazionale degli Studi Sociali Guido Carli) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.