Nipon Theera‐Umpon
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Biophysics top 2%
- Co-authors
- Sansanee AuephanwiriyakulSompong DhompongsaKeun Ho RyuVan-Huy PhamPaul GaderSanghyuk LeeJonglak PahasaYongjun Piao
- Topics
- Digital Imaging for Blood Diseases (13 papers)Neural Networks and Applications (13 papers)AI in cancer detection (11 papers)
- Partner nations
- ThailandSouth KoreaVietnam
In The Last Decade
Nipon Theera‐Umpon
120 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 156
- Artificial Intelligence 620
- Computer Vision and Pattern Recognition 572
- Radiology, Nuclear Medicine and Imaging 205
- Biomedical Engineering 133
- Biophysics 121
Countries citing papers authored by Nipon Theera‐Umpon
This map shows the geographic impact of Nipon Theera‐Umpon'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 Nipon Theera‐Umpon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nipon Theera‐Umpon more than expected).
Fields of papers citing papers by Nipon Theera‐Umpon
This network shows the impact of papers produced by Nipon Theera‐Umpon. 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 Nipon Theera‐Umpon. The network helps show where Nipon Theera‐Umpon may publish in the future.
Co-authorship network of co-authors of Nipon Theera‐Umpon
This figure shows the co-authorship network connecting the top 25 collaborators of Nipon Theera‐Umpon. A scholar is included among the top collaborators of Nipon Theera‐Umpon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nipon Theera‐Umpon. Nipon Theera‐Umpon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 31 | |
| 9 | 8 | |
| 10 | 22 | |
| 11 | 8 | |
| 12 | 2 | |
| 13 | 3 | |
| 14 | Foot and ankle problems in Thai monks. | 2 |
| 15 | Foot and ankle problems in Muay Thai kickboxers. | 9 |
| 16 | Examination of Mammogram Image Classification using Fuzzy Co-occurrence Matrix | 1 |
| 17 | 58 | |
| 18 | Buried Unexploded Ordnance Detection Using Energy-Based Features of Ground Penetrating Radar Signals | 1 |
| 19 | Automatic White Blood Cell Classification Using Biased-Output Neural Networks with Morphological Features | 6 |
| 20 | Thai Phoneme Segmentation using Dual-Band Energy Contour | 8 |
About Nipon Theera‐Umpon
Nipon Theera‐Umpon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 128 papers that have together received 1.5k indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (13 papers), Neural Networks and Applications (13 papers) and AI in cancer detection (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (572 citations), Health Information Management (102 citations) and Biophysics (121 citations). Nipon Theera‐Umpon has collaborated with scholars based in Thailand, South Korea and Vietnam. Frequent co-authors include Sansanee Auephanwiriyakul, Sompong Dhompongsa, Keun Ho Ryu, Van-Huy Pham, Paul Gader, Sanghyuk Lee, Jonglak Pahasa, Yongjun Piao, Direk Patikulsila and Meijing Li. Their work appears in journals such as Environmental Pollution, Expert Systems with Applications and IEEE Access.
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.