Jinn‐Min Yang
Impact in
- Media Technology top 1%
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
- Atmospheric Science top 10%
- Remote Sensing and Land Use
Papers in
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- Remote-Sensing Image Classification 12
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- Remote Sensing and Land Use 8
- Co-authors
- Bor‐Chen Kuo (9 shared papers)Pao-Ta Yu (5 shared papers)Cheng‐Hsuan Li (1 shared paper)Chun‐Hsiang Chuang (2 shared papers)Szu‐Wei Yang (1 shared paper)Tian-Wei Sheu (1 shared paper)Hsiao‐Yun Huang (1 shared paper)Ming-Hsiang Su (1 shared paper)
- Journals
- IEEE Transactions on Geoscience and Remote Sensing (3 papers)Educational Technology & Society (1 paper)Journal of Convergence Information Technology (1 paper)UTS ePRESS (University of Technology Sydney) (1 paper)
- Partner nations
- TaiwanUnited States
In The Last Decade
Jinn‐Min Yang
15 papers receiving 353 citations
Peers
Comparison fields: 5 of 50
- Media Technology 304
- Atmospheric Science 218
- Analytical Chemistry 83
- Computer Vision and Pattern Recognition 107
- Artificial Intelligence 45
Countries citing papers authored by Jinn‐Min Yang
This map shows the geographic impact of Jinn‐Min Yang'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 Jinn‐Min Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinn‐Min Yang more than expected).
Fields of papers citing papers by Jinn‐Min Yang
This network shows the impact of papers produced by Jinn‐Min Yang. 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 Jinn‐Min Yang. The network helps show where Jinn‐Min Yang may publish in the future.
Co-authors
The 18 scholars most cited alongside Jinn‐Min Yang, 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 | 2009 | 141 | |
| 2 | 2009 | 118 | |
| 3 | 2010 | 47 | |
| 4 | 2008 | 27 | |
| 5 | Evaluating Knowledge Structure-based Adaptive Testing Algorithms and System Development | 2012 | 14 |
| 6 | 2007 | 6 | |
| 7 | 2012 | 5 | |
| 8 | 2004 | 4 | |
| 9 | 2009 | 3 | |
| 10 | 2012 | 3 | |
| 11 | 2010 | 2 | |
| 12 | 2011 | 1 | |
| 13 | 2012 | 1 | |
| 14 | 2007 | 1 | |
| 15 | 2009 | 1 |
About Jinn‐Min Yang
Jinn‐Min Yang is a scholar working on Media Technology, Atmospheric Science, Analytical Chemistry, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 15 papers that have together received 374 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (12 papers), Remote Sensing and Land Use (8 papers), Spectroscopy and Chemometric Analyses (7 papers), Face and Expression Recognition (5 papers), Advanced Chemical Sensor Technologies (2 papers), Image Retrieval and Classification Techniques (2 papers), Intelligent Tutoring Systems and Adaptive Learning (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Media Technology (304 citations), Atmospheric Science (218 citations), Analytical Chemistry (83 citations), Computer Vision and Pattern Recognition (107 citations) and Artificial Intelligence (45 citations). Jinn‐Min Yang has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Bor‐Chen Kuo, Pao-Ta Yu, Cheng‐Hsuan Li, Chun‐Hsiang Chuang, Szu‐Wei Yang, Tian-Wei Sheu, Hsiao‐Yun Huang, Ming-Hsiang Su, Hsin-Hua Ho and Shih-Syun Lin. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Educational Technology & Society, Journal of Convergence Information Technology and UTS ePRESS (University of Technology Sydney).
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.