Kyle Min
Impact in
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- Visual Attention and Saliency Detection
- Image and Video Quality Assessment
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
Papers in
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- Multimodal Machine Learning Applications 4
- Human Pose and Action Recognition 4
- Video Analysis and Summarization 3
- Image and Video Quality Assessment 1
- Video Surveillance and Tracking Methods 1
- Image Processing and 3D Reconstruction 1
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- Human Motion and Animation 1
- Co-authors
- Jason J. Corso (2 shared papers)Subarna Tripathi (3 shared papers)Amit K. Roy–Chowdhury (1 shared paper)Yi Li (1 shared paper)Nuno Vasconcelos (1 shared paper)Changhoon Kim (1 shared paper)Maitreya Patel (1 shared paper)Cheng Sheng (1 shared paper)
- Partner nations
- United StatesSouth KoreaItaly
In The Last Decade
Kyle Min
6 papers receiving 157 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 142
- Human-Computer Interaction 19
- Experimental and Cognitive Psychology 18
- Media Technology 9
- Sensory Systems 5
Countries citing papers authored by Kyle Min
This map shows the geographic impact of Kyle Min'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 Kyle Min with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Min more than expected).
Fields of papers citing papers by Kyle Min
This network shows the impact of papers produced by Kyle Min. 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 Kyle Min. The network helps show where Kyle Min may publish in the future.
Co-authors
The 13 scholars most cited alongside Kyle Min, 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 | 102 | |
| 2 | 2021 | 22 | |
| 3 | 2023 | 17 | |
| 4 | 2023 | 10 | |
| 5 | 2024 | 10 | |
| 6 | 2024 | 1 | |
| 7 | 2025 | 0 |
About Kyle Min
Kyle Min is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Computer Graphics and Computer-Aided Design and Infectious Diseases, having authored 7 papers that have together received 162 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (4 papers), Video Analysis and Summarization (3 papers), Computer Graphics and Visualization Techniques (1 paper), Image and Video Quality Assessment (1 paper), Video Surveillance and Tracking Methods (1 paper), Image Processing and 3D Reconstruction (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (142 citations), Human-Computer Interaction (19 citations), Experimental and Cognitive Psychology (18 citations), Media Technology (9 citations) and Sensory Systems (5 citations). Kyle Min has collaborated with scholars based in United States, South Korea and Italy. Frequent co-authors include Jason J. Corso, Subarna Tripathi, Amit K. Roy–Chowdhury, Yi Li, Nuno Vasconcelos, Changhoon Kim, Maitreya Patel, Cheng Sheng, Giovanni Maria Farinella and Pavan Turaga.
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.