Cheng-Fa Tsai

417 total citations
19 papers, 208 citations indexed

About

Cheng-Fa Tsai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Cheng-Fa Tsai has authored 19 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Signal Processing. Recurrent topics in Cheng-Fa Tsai's work include Advanced Clustering Algorithms Research (7 papers), Data Management and Algorithms (5 papers) and Data Mining Algorithms and Applications (4 papers). Cheng-Fa Tsai is often cited by papers focused on Advanced Clustering Algorithms Research (7 papers), Data Management and Algorithms (5 papers) and Data Mining Algorithms and Applications (4 papers). Cheng-Fa Tsai collaborates with scholars based in Taiwan, Thailand and China. Cheng-Fa Tsai's co-authors include Chia-En Tsai, Chun‐Wei Tsai, Ning-Han Liu, C.C. Hsieh, W.C. Chang, C. W. Shih, H. W. Chang, Chua‐Chin Wang, Youfu Li and Yi‐Ching Huang and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Journal of Magnetism and Magnetic Materials.

In The Last Decade

Cheng-Fa Tsai

18 papers receiving 195 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Cheng-Fa Tsai Taiwan 8 82 80 34 31 28 19 208
Jason Wood United Kingdom 6 102 1.2× 46 0.6× 14 0.4× 13 0.4× 9 0.3× 13 220
Dong‐Gi Lee South Korea 10 42 0.5× 38 0.5× 12 0.4× 15 0.5× 11 0.4× 33 252
Inmaculada Tomeo-Reyes Australia 11 208 2.5× 134 1.7× 47 1.4× 32 1.0× 45 1.6× 27 358
César O. Torres Colombia 9 135 1.6× 39 0.5× 17 0.5× 6 0.2× 19 0.7× 61 254
Parvathi Chundi United States 9 27 0.3× 83 1.0× 30 0.9× 58 1.9× 13 0.5× 53 253
Rajesh Rohilla India 9 133 1.6× 70 0.9× 20 0.6× 50 1.6× 25 0.9× 35 269
Sihui Luo China 8 91 1.1× 256 3.2× 9 0.3× 14 0.5× 7 0.3× 17 377
Shuai Zhao China 10 37 0.5× 153 1.9× 32 0.9× 18 0.6× 4 0.1× 41 246
Jinghao Zhang China 9 174 2.1× 145 1.8× 14 0.4× 171 5.5× 11 0.4× 22 359
Jiaqing Liang China 12 30 0.4× 233 2.9× 5 0.1× 64 2.1× 8 0.3× 57 337

Countries citing papers authored by Cheng-Fa Tsai

Since Specialization
Citations

This map shows the geographic impact of Cheng-Fa Tsai'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-Fa Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng-Fa Tsai more than expected).

Fields of papers citing papers by Cheng-Fa Tsai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng-Fa Tsai. 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-Fa Tsai. The network helps show where Cheng-Fa Tsai may publish in the future.

Co-authorship network of co-authors of Cheng-Fa Tsai

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng-Fa Tsai. A scholar is included among the top collaborators of Cheng-Fa Tsai 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 Cheng-Fa Tsai. Cheng-Fa Tsai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Tsai, Cheng-Fa, et al.. (2024). Optimizing Deep Learning for Diabetic Retinopathy Diagnosis. International Journal of Advanced Computer Science and Applications. 15(11).
2.
Tsai, Cheng-Fa, et al.. (2023). Human Action Recognition by Deep Learning Technique with Multiple-Searching Genetic Algorithm. 125. 42–46. 1 indexed citations
3.
Tsai, Cheng-Fa, et al.. (2020). Analyzing Lung Disease Using Highly Effective Deep Learning Techniques. Healthcare. 8(2). 107–107. 30 indexed citations
4.
Tsai, Cheng-Fa, et al.. (2020). Analyzing Malaria Disease Using Effective Deep Learning Approach. Diagnostics. 10(10). 744–744. 50 indexed citations
5.
Tsai, Cheng-Fa, Yu-Chieh Chen, & Chia-En Tsai. (2019). Real Life Image Recognition of Panama Disease by an Effective Deep Learning Approach. 1–5. 4 indexed citations
6.
7.
Tsai, Cheng-Fa, et al.. (2016). Enhancement of data clustering using TSS-DBSCAN approach for data mining. 4029. 535–540. 3 indexed citations
8.
Tsai, Cheng-Fa, et al.. (2014). A Comparison of Filter and WrapperApproaches with Data Mining Techniques forCategorical Variables Selection. International Journal of Innovative Research in Computer and Communication Engineering. 2(6). 4501–4508. 8 indexed citations
9.
Chang, H. W., et al.. (2013). Magnetic properties enhancement of melt spun CoZrB ribbons by elemental substitutions. Journal of Magnetism and Magnetic Materials. 346. 74–77. 23 indexed citations
10.
11.
Tsai, Cheng-Fa, et al.. (2012). QIDBSCAN: A Quick Density-Based Clustering Technique. 4029. 638–641. 9 indexed citations
12.
Liu, Ning-Han, et al.. (2009). An intelligent music playlist generator based on the time parameter with artificial neural networks. Expert Systems with Applications. 37(4). 2815–2825. 14 indexed citations
13.
Tsai, Cheng-Fa, et al.. (2009). GF-DBSCAN: a new efficient and effective data clustering technique for large databases. 231–236. 15 indexed citations
14.
Tsai, Cheng-Fa & Yi‐Ching Huang. (2009). DDCT: detecting density differences using a novel clustering technique. 243–248. 2 indexed citations
15.
Tsai, Cheng-Fa, et al.. (2008). Gray Image Compression Using New Hierarchical Self-Organizing Map Technique. 544–544. 5 indexed citations
16.
Tsai, Cheng-Fa, et al.. (2007). FICA: A New Data Clustering Technique Based on Partitional Approach for Data Mining. 4029. 739–744. 1 indexed citations
17.
Tsai, Cheng-Fa, et al.. (2003). A new data clustering approach for data mining in large databases. 315–320. 32 indexed citations
18.
Wang, Chua‐Chin & Cheng-Fa Tsai. (2000). Fuzzy data processing using polynomial bidirectional hetero-associative network. Information Sciences. 125(1-4). 167–179. 2 indexed citations
19.
Wang, Chua‐Chin & Cheng-Fa Tsai. (1999). Polynomial bidirectional hetero-correlator. Electronics Letters. 35(23). 2039–2041. 1 indexed citations

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.

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