Yumin Suh

694 citations
13 papers · 196 · h-index 6

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Graph Theory and Algorithms
    • Advanced Neural Network Applications
    • Human Pose and Action Recognition
    • Domain Adaptation and Few-Shot Learning
    • Advanced Graph Neural Networks

Papers in

Journals
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2 papers)arXiv (Cornell University) (1 paper)

In The Last Decade

Yumin Suh

12 papers receiving 191 citations

Peers

Yumin Suh
Comparison fields: 5 of 35
  • Computer Vision and Pattern Recognition 142
  • Artificial Intelligence 110
  • Signal Processing 25
  • Space and Planetary Science 1
  • Aerospace Engineering 17
Replace Xavier Cortés with:
Xavier Cortés Spain
Adel Bibi Saudi Arabia
Apoorv Vyas Switzerland
Vikas Verma Finland
Ben Harwood Australia
Suraj Srinivas India
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Citations per field
00.5×10×15×20×24×
Xavier Cortés · 1×
Citations per year

Countries citing papers authored by Yumin Suh

Since Specialization
Citations

This map shows the geographic impact of Yumin Suh'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 Yumin Suh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yumin Suh more than expected).

Fields of papers citing papers by Yumin Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yumin Suh. 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 Yumin Suh. The network helps show where Yumin Suh may publish in the future.

Co-authors

The 23 scholars most cited alongside Yumin Suh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yumin Suh Line = papers co-authored together Yumin Suh links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201981
2 201536
3 202220
4 202219
5 201518
6 20245
7 20234
8
Morphology and reproduction of some species of Ceramium (Rhodophyta) in culture
19844
9 20234
10 20243
11
Learning to Optimize Domain Specific Normalization with Domain Augmentation for Domain Generalization
20191
12 20231
13 20240

About Yumin Suh

Yumin Suh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Information Systems, having authored 13 papers that have together received 196 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (5 papers), Data Management and Algorithms (2 papers), Graph Theory and Algorithms (2 papers), Natural Language Processing Techniques (1 paper), Cloud Computing and Resource Management (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (142 citations), Artificial Intelligence (110 citations), Signal Processing (25 citations), Space and Planetary Science (1 citation) and Aerospace Engineering (17 citations). Yumin Suh has collaborated with scholars based in United States, South Korea and Netherlands. Frequent co-authors include Kyoung Mu Lee, Wonsik Kim, Bohyung Han, Samuel Schulter, Manmohan Chandraker, Masoud Faraki, Amit K. Roy–Chowdhury, Christian Simon, Yi‐Hsuan Tsai and Yu Xiang. Their work appears in journals such as 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

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.

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