Cheng‐Yuan Liou
- Artificial Intelligence top 5%
- Neural Networks and Applications 20
- Topic Modeling 3
- Signal Processing top 10%
- Blind Source Separation Techniques 5
- Speech and Audio Processing 3
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- Fractal and DNA sequence analysis 5
- Machine Learning in Bioinformatics 3
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- Neural dynamics and brain function 4
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- 3D Shape Modeling and Analysis 4
- Co-authors
- Wei‐Chen ChengJiun-Wei LiouDaw-Ran LiouChih-Cheng HsiehHsin-Chang YangBruce R. MusicusJohn A. D. AstonRoger N. Gunn
- Partner nations
- TaiwanUnited KingdomUnited States
In The Last Decade
Cheng‐Yuan Liou
37 papers receiving 680 citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 158
- Artificial Intelligence 224
- Signal Processing 69
- Computer Graphics and Computer-Aided Design 12
- Biomedical Engineering 130
Countries citing papers authored by Cheng‐Yuan Liou
This map shows the geographic impact of Cheng‐Yuan Liou'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 Cheng‐Yuan Liou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng‐Yuan Liou more than expected).
Fields of papers citing papers by Cheng‐Yuan Liou
This network shows the impact of papers produced by Cheng‐Yuan Liou. 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 Cheng‐Yuan Liou. The network helps show where Cheng‐Yuan Liou may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Cheng‐Yuan Liou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 3 | |
| 2 | Autoencoder for wordsbreakdown → | 2014 | 337 |
| 3 | 2013 | 101 | |
| 4 | 2013 | 1 | |
| 5 | 2011 | 6 | |
| 6 | 2010 | 2 | |
| 7 | 2008 | 20 | |
| 8 | 2008 | 6 | |
| 9 | 2008 | 95 | |
| 10 | Reverse Engineering Approach in Molecular Evolution: Simulation and Case Study with Enzyme Proteins. | 2006 | 1 |
| 11 | Geometrical Perspective on Learning Behavior | 2005 | 1 |
| 12 | 2000 | 8 | |
| 13 | 1999 | 14 | |
| 14 | 1999 | 7 | |
| 15 | Self-Relaxation for Multilayer Perceptron | 1998 | 1 |
| 16 | 1997 | 0 | |
| 17 | Numerical soap film for the Steiner tree problem | 1996 | 1 |
| 18 | Meshed snakes | 1996 | 1 |
| 19 | 1990 | 2 | |
| 20 | 1989 | 2 |
About Cheng‐Yuan Liou
Cheng‐Yuan Liou is a scholar working on Computer Graphics and Computer-Aided Design, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 48 papers that have together received 707 indexed citations. Recurring topics across this work include Neural Networks and Applications (20 papers), Blind Source Separation Techniques (5 papers), Fractal and DNA sequence analysis (5 papers), Neural dynamics and brain function (4 papers), 3D Shape Modeling and Analysis (4 papers), Machine Learning in Bioinformatics (3 papers), Speech and Audio Processing (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (158 citations), Artificial Intelligence (224 citations), Signal Processing (69 citations), Computer Graphics and Computer-Aided Design (12 citations) and Biomedical Engineering (130 citations). Cheng‐Yuan Liou has collaborated with scholars based in Taiwan, United Kingdom and United States. Frequent co-authors include Wei‐Chen Cheng, Jiun-Wei Liou, Daw-Ran Liou, Chih-Cheng Hsieh, Hsin-Chang Yang, Bruce R. Musicus, John A. D. Aston, Roger N. Gunn, John Ashburner and Chia‐Ying Lee. Their work appears in journals such as Neural Networks, Neurocomputing, The Visual Computer, Mechanical Systems and Signal Processing and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.