Shih‐Lin Hung

2.0k total citations
50 papers, 1.6k citations indexed

About

Shih‐Lin Hung is a scholar working on Civil and Structural Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shih‐Lin Hung has authored 50 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Civil and Structural Engineering, 23 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shih‐Lin Hung's work include Structural Health Monitoring Techniques (23 papers), Neural Networks and Applications (18 papers) and Ultrasonics and Acoustic Wave Propagation (6 papers). Shih‐Lin Hung is often cited by papers focused on Structural Health Monitoring Techniques (23 papers), Neural Networks and Applications (18 papers) and Ultrasonics and Acoustic Wave Propagation (6 papers). Shih‐Lin Hung collaborates with scholars based in Taiwan, United States and Myanmar. Shih‐Lin Hung's co-authors include Hojjat Adeli, Chengnian Huang, Ching‐Sheng Huang, Su Wei, Tzu-Hsuan Lin, J.C. Chern, Chiung‐Shiann Huang, Der‐Cherng Tarng, Y.-J. Huang and Rebecca Wu and has published in prestigious journals such as Expert Systems with Applications, Sensors and Actuators B Chemical and American Journal of Kidney Diseases.

In The Last Decade

Shih‐Lin Hung

47 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shih‐Lin Hung Taiwan	22	720	439	240	167	151	50	1.6k
S. N. Omkar India	21	347 0.5×	260 0.6×	249 1.0×	136 0.8×	144 1.0×	83	1.4k
Andrew Starr United Kingdom	21	278 0.4×	146 0.3×	379 1.6×	186 1.1×	71 0.5×	119	1.7k
Sean Brennan United States	22	272 0.4×	123 0.3×	522 2.2×	242 1.4×	186 1.2×	146	1.6k
Armin Dadras Eslamlou Iran	20	1.1k 1.5×	588 1.3×	144 0.6×	155 0.9×	117 0.8×	37	2.0k
Mahdi Eftekhari Iran	23	180 0.3×	590 1.3×	194 0.8×	101 0.6×	259 1.7×	135	1.5k
Yılmaz Kaya Türkiye	23	137 0.2×	472 1.1×	408 1.7×	152 0.9×	283 1.9×	62	1.5k
Shima Rashidi Iraq	21	219 0.3×	302 0.7×	73 0.3×	152 0.9×	115 0.8×	42	1.2k
Orhan Yaman Türkiye	19	143 0.2×	227 0.5×	208 0.9×	131 0.8×	163 1.1×	76	1.2k
Luis Vergara Spain	24	128 0.2×	405 0.9×	100 0.4×	114 0.7×	234 1.5×	132	1.5k
Paolo Sommella Italy	22	189 0.3×	281 0.6×	201 0.8×	205 1.2×	150 1.0×	117	1.3k

Countries citing papers authored by Shih‐Lin Hung

Since Specialization

Citations

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

Fields of papers citing papers by Shih‐Lin Hung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih‐Lin Hung. 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 Shih‐Lin Hung. The network helps show where Shih‐Lin Hung may publish in the future.

Co-authorship network of co-authors of Shih‐Lin Hung

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

All Works

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20 of 20 papers shown

Hung, Shih‐Lin, et al.. (2024). Application of the artificial neural network and enhanced particle swarm optimization to model updating of structures. Journal of Civil Structural Health Monitoring. 15(1). 59–86. 1 indexed citations

Lee, L. C., et al.. (2022). Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan. Earth and Space Science. 9(9). 13 indexed citations

Hung, Shih‐Lin, et al.. (2022). Constrained K-means and Genetic Algorithm-based Approaches for Optimal Placement of Wireless Structural Health Monitoring Sensors. Civil Engineering Journal. 8(12). 2675–2692. 13 indexed citations

Hung, Shih‐Lin, et al.. (2020). A Displacement Frequency Response Function‐Based Approach for Locating Damage to Building Structures. Advances in Civil Engineering. 2020(1). 3 indexed citations

Hung, Shih‐Lin, et al.. (2015). Combining subspace approach and short time Fourier analysis for locating structural damage storeys. Journal of Vibroengineering. 17(5). 2480–2490. 2 indexed citations

Lin, Tzu-Hsuan, et al.. (2010). Towards Development of Wireless Sensor System for Monitoring Anesthetic Agents. Sensor Letters. 8(6). 767–776. 1 indexed citations

Chavali, Murthy, et al.. (2007). Active 433 MHz-W UHF RF-powered chip integrated with a nanocomposite m-MWCNT/polypyrrole sensor for wireless monitoring of volatile anesthetic agent sevoflurane. Sensors and Actuators A Physical. 141(1). 109–119. 16 indexed citations

Hung, Shih‐Lin, et al.. (2006). STEEL BRIDGE CORROSION DETECTION BY WAVELET TRANSFORM THEORY. 5 indexed citations

Lai, Yu‐Lin, et al.. (2006). Areca nut extracts reduce the intracellular reactive oxygen species and release of myeloperoxidase by human polymorphonuclear leukocytes. Journal of Periodontal Research. 42(1). 69–76. 22 indexed citations

10.

Hung, Shih‐Lin, et al.. (2006). Association Between Transferrin Receptor–Ferritin Index and Conventional Measures of Iron Responsiveness in Hemodialysis Patients. American Journal of Kidney Diseases. 47(6). 1036–1044. 30 indexed citations

11.

Hung, Shih‐Lin, et al.. (2005). A neural network-based approach for detection of structural damage. international conference on Modelling and simulation. 251–256. 3 indexed citations

12.

Huang, Ching‐Sheng, et al.. (2005). A Wavelet-Based Approach to Identifying Structural Modal Parameters from Seismic Response and Free Vibration Data. Computer-Aided Civil and Infrastructure Engineering. 20(6). 408–423. 30 indexed citations

13.

Hung, Shih‐Lin, et al.. (2005). Unsupervised fuzzy neural networks for damage detection of structures. Structural Control and Health Monitoring. 14(1). 144–161. 34 indexed citations

14.

Hung, Shih‐Lin, et al.. (2002). Machine learning in engineering design-an unsupervised fuzzy neural network case-based learning model. 1. 156–160. 1 indexed citations

15.

Huang, Chengnian, et al.. (2002). A neural network approach for structural identification and diagnosis of a building from seismic response data. Earthquake Engineering & Structural Dynamics. 32(2). 187–206. 102 indexed citations

16.

Hung, Shih‐Lin, et al.. (2001). High-order MS CMAC neural network. IEEE Transactions on Neural Networks. 12(3). 598–603. 68 indexed citations

17.

Hung, Shih‐Lin & Hojjat Adeli. (1994). A parallel genetic/neural network learning algorithm for MIMD shared memory machines. IEEE Transactions on Neural Networks. 5(6). 900–909. 114 indexed citations

18.

Adeli, Hojjat & Shih‐Lin Hung. (1994). Machine Learning: Neural Networks, Genetic Algorithms, and Fuzzy Systems. Medical Entomology and Zoology. 261 indexed citations

19.

Hung, Shih‐Lin. (1992). Neural network and genetic learning algorithms for computer-aided design and pattern recognition. OhioLink ETD Center (Ohio Library and Information Network). 1 indexed citations

20.

Hung, Shih‐Lin & Hojjat Adeli. (1991). A Neural Network Environment for Intelligent CAD. 93–97. 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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