Jyh-Horng Jeng
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Mathematical Physics top 5%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Jer‐Guang HsiehTrieu‐Kien TruongYih-Lon LinChun‐Chieh TsengI.S. ReedMing‐Chia HsiehShu‐Ling ChengChien‐Hua Chen
- Topics
- Mathematical Dynamics and Fractals (13 papers)Neural Networks and Applications (11 papers)Cellular Automata and Applications (8 papers)
- Partner nations
- TaiwanPhilippinesUnited States
In The Last Decade
Jyh-Horng Jeng
67 papers receiving 964 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 476
- Computer Vision and Pattern Recognition 367
- Mathematical Physics 276
- Computational Theory and Mathematics 100
- Computer Networks and Communications 84
Countries citing papers authored by Jyh-Horng Jeng
This map shows the geographic impact of Jyh-Horng Jeng'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 Jyh-Horng Jeng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jyh-Horng Jeng more than expected).
Fields of papers citing papers by Jyh-Horng Jeng
This network shows the impact of papers produced by Jyh-Horng Jeng. 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 Jyh-Horng Jeng. The network helps show where Jyh-Horng Jeng may publish in the future.
Co-authorship network of co-authors of Jyh-Horng Jeng
This figure shows the co-authorship network connecting the top 25 collaborators of Jyh-Horng Jeng. A scholar is included among the top collaborators of Jyh-Horng Jeng 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 Jyh-Horng Jeng. Jyh-Horng Jeng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 12 | |
| 3 | 10 | |
| 4 | 25 | |
| 5 | 15 | |
| 6 | 19 | |
| 7 | A Study on Combined CNN-SVM Model for Visual Object Recognition. | 1 |
| 8 | Entropy Improvement for Fractal Image Coder | 2 |
| 9 | 9 | |
| 10 | 14 | |
| 11 | 10 | |
| 12 | 11 | |
| 13 | 51 | |
| 14 | 60 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | Characterization of canonical robust template values for a class of uncoupled CNNs implementing linearly separable Boolean functions | 0 |
| 18 | 46 | |
| 19 | 53 | |
| 20 | 3 |
About Jyh-Horng Jeng
Jyh-Horng Jeng is a scholar working on Mathematical Physics, Computer Vision and Pattern Recognition and Health Information Management, having authored 70 papers that have together received 1.1k indexed citations. Recurring topics across this work include Mathematical Dynamics and Fractals (13 papers), Neural Networks and Applications (11 papers) and Cellular Automata and Applications (8 papers). The work is most often cited by research in Mathematical Physics (276 citations), Computer Vision and Pattern Recognition (367 citations) and Artificial Intelligence (476 citations). Jyh-Horng Jeng has collaborated with scholars based in Taiwan, Philippines and United States. Frequent co-authors include Jer‐Guang Hsieh, Trieu‐Kien Truong, Yih-Lon Lin, Chun‐Chieh Tseng, I.S. Reed, Ming‐Chia Hsieh, Shu‐Ling Cheng, Chien‐Hua Chen, Chih‐Wen Wang and Chien‐Hua Chen. Their work appears in journals such as Scientific Reports, 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.