Fang-Rong Hsu
- Molecular Biology
- Plant Science
- Computer Vision and Pattern Recognition
- Artificial Intelligence
- Computational Theory and Mathematics top 10%
- Co-authors
- Wei-Chung ShiaWen‐Ching WangPei‐Ching ChangHsing-Jien KungChun-Eng LiuHuang‐Chi ChenChang‐Hua ChenMing-Feng Hsieh
- Topics
- RNA and protein synthesis mechanisms (7 papers)Advanced Graph Theory Research (6 papers)Complexity and Algorithms in Graphs (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Access
In The Last Decade
Fang-Rong Hsu
37 papers receiving 425 citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Molecular Biology 130
- Plant Science 65
- Computer Vision and Pattern Recognition 56
- Artificial Intelligence 48
- Computational Theory and Mathematics 43
Countries citing papers authored by Fang-Rong Hsu
This map shows the geographic impact of Fang-Rong Hsu'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 Fang-Rong Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang-Rong Hsu more than expected).
Fields of papers citing papers by Fang-Rong Hsu
This network shows the impact of papers produced by Fang-Rong Hsu. 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 Fang-Rong Hsu. The network helps show where Fang-Rong Hsu may publish in the future.
Co-authorship network of co-authors of Fang-Rong Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Fang-Rong Hsu. A scholar is included among the top collaborators of Fang-Rong Hsu 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 Fang-Rong Hsu. Fang-Rong Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | EFFResNet-ViT: A Fusion-Based Convolutional and Vision Transformer Model for Explainable Medical Image Classificationbreakdown → | 20 |
| 2 | 0 | |
| 3 | 12 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 26 | |
| 10 | 14 | |
| 11 | 10 | |
| 12 | 11 | |
| 13 | 4 | |
| 14 | 19 | |
| 15 | 3 | |
| 16 | 111 | |
| 17 | 34 | |
| 18 | Some Optimal Parallel Algorithms on Interval and Circular-Arc Graphs | 7 |
| 19 | 7 | |
| 20 | 19 |
About Fang-Rong Hsu
Fang-Rong Hsu is a scholar working on Health Informatics, Computer Graphics and Computer-Aided Design and Computational Theory and Mathematics, having authored 41 papers that have together received 443 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (7 papers), Advanced Graph Theory Research (6 papers) and Complexity and Algorithms in Graphs (5 papers). The work is most often cited by research in Molecular Medicine (27 citations), Endocrinology (21 citations) and Health Informatics (4 citations). Fang-Rong Hsu has collaborated with scholars based in Taiwan, China and Japan. Frequent co-authors include Wei-Chung Shia, Wen‐Ching Wang, Pei‐Ching Chang, Hsing-Jien Kung, Chun-Eng Liu, Huang‐Chi Chen, Chang‐Hua Chen, Ming-Feng Hsieh, Chuan-Yi Tang and Hwei‐Ling Peng. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE 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.