Liang-Sian Lin

417 total citations
34 papers, 323 citations indexed

About

Liang-Sian Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Liang-Sian Lin has authored 34 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Liang-Sian Lin's work include Imbalanced Data Classification Techniques (8 papers), Machine Learning and Data Classification (7 papers) and Face and Expression Recognition (7 papers). Liang-Sian Lin is often cited by papers focused on Imbalanced Data Classification Techniques (8 papers), Machine Learning and Data Classification (7 papers) and Face and Expression Recognition (7 papers). Liang-Sian Lin collaborates with scholars based in Taiwan, Singapore and China. Liang-Sian Lin's co-authors include Der‐Chiang Li, Chien-Chih Chen, Jong‐Wuu Wu, J. T. Guthrie, Susan C. Hu, Longbing Cao, Tung‐I Tsai, Chengqi Zhang, Yu-Xiang Wang and Chih‐Ching Lin and has published in prestigious journals such as PLoS ONE, European Journal of Operational Research and Journal of Membrane Science.

In The Last Decade

Liang-Sian Lin

30 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liang-Sian Lin Taiwan 11 127 62 57 50 36 34 323
Jörg Gebhardt Germany 10 152 1.2× 16 0.3× 28 0.5× 66 1.3× 80 2.2× 31 365
Andrés Gómez United States 10 42 0.3× 31 0.5× 20 0.4× 60 1.2× 46 1.3× 34 285
Philipp Limbourg Germany 9 98 0.8× 178 2.9× 20 0.4× 48 1.0× 45 1.3× 14 391
Severino F. Galán Spain 11 171 1.3× 46 0.7× 7 0.1× 37 0.7× 24 0.7× 18 323
Krzysztof Trawiński Spain 9 133 1.0× 13 0.2× 17 0.3× 32 0.6× 18 0.5× 21 271
Henrik Linusson Sweden 9 129 1.0× 12 0.2× 39 0.7× 15 0.3× 34 0.9× 15 264
An‐Da Li China 8 196 1.5× 32 0.5× 7 0.1× 21 0.4× 49 1.4× 16 355
Selin Damla Ahipaşaoğlu Singapore 10 73 0.6× 19 0.3× 20 0.4× 57 1.1× 36 1.0× 26 302
Mohamed Jaward Bah China 4 250 2.0× 10 0.2× 30 0.5× 13 0.3× 51 1.4× 14 367
Vijitashwa Pandey United States 8 42 0.3× 114 1.8× 8 0.1× 52 1.0× 28 0.8× 70 352

Countries citing papers authored by Liang-Sian Lin

Since Specialization
Citations

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

Fields of papers citing papers by Liang-Sian Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang-Sian Lin. 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 Liang-Sian Lin. The network helps show where Liang-Sian Lin may publish in the future.

Co-authorship network of co-authors of Liang-Sian Lin

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

All Works

20 of 20 papers shown
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Lin, Liang-Sian, et al.. (2023). Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation. Decision Support Systems. 172. 113996–113996. 6 indexed citations
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Lin, Liang-Sian, et al.. (2023). Generating virtual samples to improve learning performance in small datasets with non-linear and asymmetric distributions. Neurocomputing. 548. 126408–126408. 4 indexed citations
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Lin, Liang-Sian, et al.. (2023). Driver Fatigue Detection Using TGAM EEG Signal Processing Module. 984–986. 1 indexed citations
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Wang, Yu-Xiang, et al.. (2023). EEG Analyzing Color Temperature Influence on Emotions Based on TGAM Module. 441–444. 2 indexed citations
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Kuo, R.J., Liang-Sian Lin, Ferani E. Zulvia, & Chih‐Ching Lin. (2017). Integration of cluster analysis and granular computing for imbalanced data classification: A case study on prostate cancer prognosis in Taiwan. Journal of Intelligent & Fuzzy Systems. 32(3). 2251–2267. 4 indexed citations
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Li, Der‐Chiang, et al.. (2017). Detecting representative data and generating synthetic samples to improve learning accuracy with imbalanced data sets. PLoS ONE. 12(8). e0181853–e0181853. 27 indexed citations
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Li, Der‐Chiang, et al.. (2017). Rebuilding sample distributions for small dataset learning. Decision Support Systems. 105. 66–76. 35 indexed citations
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Li, Der‐Chiang, et al.. (2016). The attribute-trend-similarity method to improve learning performance for small datasets. International Journal of Production Research. 55(7). 1898–1913. 20 indexed citations
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Lin, Liang-Sian, Der‐Chiang Li, Weihao Yu, & Yu‐Mei Hsueh. (2015). Generating Multi-modality Virtual Samples with Soft DBSCAN for Small Data Set Learning. 363–368. 1 indexed citations
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Li, Der‐Chiang & Liang-Sian Lin. (2014). Generating information for small data sets with a multi-modal distribution. Decision Support Systems. 66. 71–81. 23 indexed citations
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Li, Der‐Chiang, et al.. (2013). A learning method for small data sets with multimodality variables. 36. 481–483. 1 indexed citations
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Li, Der‐Chiang & Liang-Sian Lin. (2013). A new approach to assess product lifetime performance for small data sets. European Journal of Operational Research. 230(2). 290–298. 28 indexed citations
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Wu, Jong‐Wuu, et al.. (2010). Assessing the lifetime performance index of Rayleigh products based on the Bayesian estimation under progressive type II right censored samples. Journal of Computational and Applied Mathematics. 235(6). 1676–1688. 51 indexed citations
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Lin, Liang-Sian, et al.. (2004). The Applications Of Genetic Algorithms InStock Market Data Mining Optimisation. WIT transactions on information and communication technologies. 33. 12 indexed citations
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Lin, Liang-Sian & J. T. Guthrie. (2000). Preparation and characterisation of novel, blood-plasma-separation membranes for use in biosensors. Journal of Membrane Science. 173(1). 73–85. 19 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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