Ching-Hwa Cheng
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Hardware and Architecture top 5%
- Biomedical Engineering
- Artificial Intelligence
- Co-authors
- Don‐Gey LiuShambhu UpadhyayaMing-Chien TsaiThanh-Tuan NguyenJiun-In GuoFeng-Tso ChienChien‐Chang LinHsien‐Chin Chiu
- Topics
- VLSI and Analog Circuit Testing (16 papers)Low-power high-performance VLSI design (16 papers)Advancements in Semiconductor Devices and Circuit Design (11 papers)
- Partner nations
- TaiwanVietnamUnited States
In The Last Decade
Ching-Hwa Cheng
59 papers receiving 427 citations
Peers
Comparison fields: 5 of 72
- Electrical and Electronic Engineering 181
- Computer Vision and Pattern Recognition 121
- Hardware and Architecture 100
- Biomedical Engineering 82
- Artificial Intelligence 69
Countries citing papers authored by Ching-Hwa Cheng
This map shows the geographic impact of Ching-Hwa 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 Ching-Hwa Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ching-Hwa Cheng more than expected).
Fields of papers citing papers by Ching-Hwa Cheng
This network shows the impact of papers produced by Ching-Hwa 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 Ching-Hwa Cheng. The network helps show where Ching-Hwa Cheng may publish in the future.
Co-authorship network of co-authors of Ching-Hwa Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Hwa Cheng. A scholar is included among the top collaborators of Ching-Hwa 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 Ching-Hwa Cheng. Ching-Hwa 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 | 1 | |
| 2 | 0 | |
| 3 | 12 | |
| 4 | 49 | |
| 5 | 30 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | Using voltage-difference to design a dual-voltage low-power multiple-mode video decoder | 1 |
| 13 | 0 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 0 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 1 |
About Ching-Hwa Cheng
Ching-Hwa Cheng is a scholar working on Hardware and Architecture, Instrumentation and Computer Vision and Pattern Recognition, having authored 72 papers that have together received 442 indexed citations. Recurring topics across this work include VLSI and Analog Circuit Testing (16 papers), Low-power high-performance VLSI design (16 papers) and Advancements in Semiconductor Devices and Circuit Design (11 papers). The work is most often cited by research in Hardware and Architecture (100 citations), Computer Vision and Pattern Recognition (121 citations) and Instrumentation (18 citations). Ching-Hwa Cheng has collaborated with scholars based in Taiwan, Vietnam and United States. Frequent co-authors include Don‐Gey Liu, Shambhu Upadhyaya, Ming-Chien Tsai, Thanh-Tuan Nguyen, Jiun-In Guo, Feng-Tso Chien, Chien‐Chang Lin, Hsien‐Chin Chiu, Desheng Chen and Yiwen Wang. Their work appears in journals such as IEEE Access, IEEE Transactions on Electron Devices and IEEE Transactions on Computers.
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.