Yu-Len Huang
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 2%
- Molecular Biology
- Co-authors
- Dar‐Ren ChenRuey‐Feng ChangWu‐Chung ShenJeon‐Hor ChenKao-Lun WangTsu‐Yi HsiehShou‐Jen KuoHwa‐Koon Wu
- Topics
- AI in cancer detection (24 papers)Radiomics and Machine Learning in Medical Imaging (13 papers)Ultrasound Imaging and Elastography (11 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingArtificial Intelligence
- Partner nations
- TaiwanChinaSouth Korea
In The Last Decade
Yu-Len Huang
59 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 566
- Radiology, Nuclear Medicine and Imaging 485
- Computer Vision and Pattern Recognition 480
- Media Technology 143
- Molecular Biology 115
Countries citing papers authored by Yu-Len Huang
This map shows the geographic impact of Yu-Len Huang'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 Yu-Len Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Len Huang more than expected).
Fields of papers citing papers by Yu-Len Huang
This network shows the impact of papers produced by Yu-Len Huang. 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 Yu-Len Huang. The network helps show where Yu-Len Huang may publish in the future.
Co-authorship network of co-authors of Yu-Len Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Len Huang. A scholar is included among the top collaborators of Yu-Len Huang 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 Yu-Len Huang. Yu-Len Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 6 | |
| 3 | 5 | |
| 4 | 8 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 36 | |
| 9 | 16 | |
| 10 | 13 | |
| 11 | 2 | |
| 12 | 75 | |
| 13 | A fast method for textural analysis of DCT-based image | 9 |
| 14 | 50 | |
| 15 | A Fast Finite-State Algorithm for Generating RGB Palettes of Color Quantized Images. | 13 |
| 16 | 5 | |
| 17 | 148 | |
| 18 | Automatic Facial Feature Extraction in Model-Based Coding. | 10 |
| 19 | 45 | |
| 20 | 139 |
About Yu-Len Huang
Yu-Len Huang is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 60 papers that have together received 1.1k indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Ultrasound Imaging and Elastography (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (480 citations), Radiology, Nuclear Medicine and Imaging (485 citations) and Artificial Intelligence (566 citations). Yu-Len Huang has collaborated with scholars based in Taiwan, China and South Korea. Frequent co-authors include Dar‐Ren Chen, Ruey‐Feng Chang, Wu‐Chung Shen, Jeon‐Hor Chen, Kao-Lun Wang, Tsu‐Yi Hsieh, Shou‐Jen Kuo, Hwa‐Koon Wu, Yi‐Hsuan Hsiao and Chia-Jen Chang. Their work appears in journals such as Scientific Reports, IEEE Transactions on Image Processing and Physics in Medicine and Biology.
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.