Minyoung Huh
Impact in
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- Digital Media Forensic Detection
- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Advanced Steganography and Watermarking Techniques
- Acoustics and Ultrasonics top 10%
Papers in
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- Digital Media Forensic Detection 3
- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image Processing Techniques 2
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- Adversarial Robustness in Machine Learning 1
- Co-authors
- Andrew Owens (1 shared paper)Andy Liu (1 shared paper)Alexei A. Efros (1 shared paper)Shaohua Sun (2 shared papers)Yuan-Hong Liao (1 shared paper)Ning Zhang (1 shared paper)Joseph J. Lim (1 shared paper)Jillian Iafrati (1 shared paper)
- Journals
- Nature Communications (1 paper)Lecture notes in computer science (3 papers)Purdue e-Pubs (Purdue University System) (1 paper)
- Partner nations
- United StatesIndiaTaiwan
In The Last Decade
Minyoung Huh
6 papers receiving 434 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 357
- Acoustics and Ultrasonics 13
- Computer Graphics and Computer-Aided Design 39
- Media Technology 74
- Biophysics 36
Countries citing papers authored by Minyoung Huh
This map shows the geographic impact of Minyoung Huh'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 Minyoung Huh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minyoung Huh more than expected).
Fields of papers citing papers by Minyoung Huh
This network shows the impact of papers produced by Minyoung Huh. 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 Minyoung Huh. The network helps show where Minyoung Huh may publish in the future.
Co-authors
The 20 scholars most cited alongside Minyoung Huh, 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 | 2018 | 302 | |
| 2 | 2018 | 88 | |
| 3 | 2019 | 34 | |
| 4 | 2019 | 20 | |
| 5 | 2022 | 2 | |
| 6 | A Study on the Analysis and Improvement of the Acoustic Characteristics of the Muffler in Compressor | 1994 | 1 |
About Minyoung Huh
Minyoung Huh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Automotive Engineering and Cellular and Molecular Neuroscience, having authored 6 papers that have together received 447 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Image Processing Techniques (2 papers), Molecular Communication and Nanonetworks (1 paper), Robotics and Sensor-Based Localization (1 paper), Engineering Applied Research (1 paper), Aerodynamics and Fluid Dynamics Research (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (357 citations), Acoustics and Ultrasonics (13 citations), Computer Graphics and Computer-Aided Design (39 citations), Media Technology (74 citations) and Biophysics (36 citations). Minyoung Huh has collaborated with scholars based in United States, India and Taiwan. Frequent co-authors include Andrew Owens, Andy Liu, Alexei A. Efros, Shaohua Sun, Yuan-Hong Liao, Ning Zhang, Joseph J. Lim, Ning Zhang, Jillian Iafrati and Maysamreza Chamanzar. Their work appears in journals such as Nature Communications, Lecture notes in computer science and Purdue e-Pubs (Purdue University System).
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.