Hsu-Yung Cheng
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 5%
- Automotive Engineering top 2%
- Electrical and Electronic Engineering
- Renewable Energy, Sustainability and the Environment top 10%
- Co-authors
- Chih-Chang YuNanning ZhengYi‐Ying ChenBor-Shenn JengJenq–Neng HwangQing LiKuo-Chin FanChih-Lung Lin
- Topics
- Video Surveillance and Tracking Methods (30 papers)Advanced Image and Video Retrieval Techniques (12 papers)Solar Radiation and Photovoltaics (9 papers)
- Journals
- Applied Physics LettersIEEE Transactions on Image ProcessingExpert Systems with Applications
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Hsu-Yung Cheng
75 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 710
- Artificial Intelligence 421
- Automotive Engineering 369
- Electrical and Electronic Engineering 295
- Renewable Energy, Sustainability and the Environment 202
Countries citing papers authored by Hsu-Yung Cheng
This map shows the geographic impact of Hsu-Yung Cheng'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 Hsu-Yung Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsu-Yung Cheng more than expected).
Fields of papers citing papers by Hsu-Yung Cheng
This network shows the impact of papers produced by Hsu-Yung Cheng. 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 Hsu-Yung Cheng. The network helps show where Hsu-Yung Cheng may publish in the future.
Co-authorship network of co-authors of Hsu-Yung Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Hsu-Yung Cheng. A scholar is included among the top collaborators of Hsu-Yung Cheng 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 Hsu-Yung Cheng. Hsu-Yung Cheng 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 | 1 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 23 | |
| 9 | 0 | |
| 10 | 36 | |
| 11 | 28 | |
| 12 | 41 | |
| 13 | 8 | |
| 14 | 155 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 35 | |
| 18 | Binarization method based on pixel-level dynamic thresholds for change detection in image sequences | 3 |
| 19 | 14 | |
| 20 | 28 |
About Hsu-Yung Cheng
Hsu-Yung Cheng is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 82 papers that have together received 1.4k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (30 papers), Advanced Image and Video Retrieval Techniques (12 papers) and Solar Radiation and Photovoltaics (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (710 citations), Automotive Engineering (369 citations) and Media Technology (156 citations). Hsu-Yung Cheng has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Chih-Chang Yu, Nanning Zheng, Yi‐Ying Chen, Bor-Shenn Jeng, Jenq–Neng Hwang, Qing Li, Kuo-Chin Fan, Chih-Lung Lin, Kuo‐Chin Fan and Lin Zhao. Their work appears in journals such as Applied Physics Letters, IEEE Transactions on Image Processing and Expert Systems with Applications.
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.